{ "channeldata_version": 1, "packages": { "_python_rc": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "See https://github.com/conda-forge/conda-forge-ci-setup-feedstock/issues/280", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/conda-forge/_python_rc-feedstock", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Unlicense", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": null, "subdirs": [ "noarch" ], "summary": "Dummy package to force selection of python_rc channel when channel_priority is set to strict", "tags": null, "text_prefix": false, "timestamp": 1695553959, "version": "1" }, "a5-miseq": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://sourceforge.net/projects/ngop", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPLv3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://sourceforge.net/projects/ngopt/files/a5_miseq_linux_20160825.tar.gz", "subdirs": [ "noarch" ], "summary": "A5-miseq is a pipeline for assembling DNA sequence data generated on the Illumina sequencing platform. 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Currently it supports processing data from HiSeq 2000/2500/3000/4000, Nextseq 500/550, MiniSeq...and other Illumina 1.8 or newer formats.", "tags": null, "text_prefix": false, "timestamp": 1694262763, "version": "0.9.7" }, "age-metasv": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/marghoob/AGE/tree/simple-parseable-output", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "CCPL (Creative Commons Public License)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/marghoob/AGE/archive/344429ccb.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "optimal alignment of sequences with structural variants (SVs), modifiied for MetaSV integration", "tags": null, "text_prefix": false, "timestamp": 1694264594, "version": "2015.01.29.3" }, "agfusion": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/murphycj/AGFusion", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/a/agfusion/agfusion-1.4.1.tar.gz", "subdirs": [ "noarch" ], "summary": "Python package to annotate and visualize gene fusions.", "tags": null, "text_prefix": true, "timestamp": 1694573002, "version": "1.4.1" }, "akt": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Ancestry and Kinship Tools (AKT) provides a handful of useful statistical genetics routines using the htslib API for input/output. This means it can seamlessly read BCF/VCF files and play nicely with bcftools.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/Illumina/akt", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "file:///root/source/v0.3.3.1.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Ancestry and Kinship Tools (AKT)", "tags": null, "text_prefix": false, "timestamp": 1696989187, "version": "0.3.3" }, "alfred": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/tobiasrausch/alfred", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "BSD-3-Clause", "post_link": false, "pre_link": false, "pre_unlink": false, 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alignlib C++ library for sequence alignment", "tags": null, "text_prefix": false, "timestamp": 1696670001, "version": "0.3" }, "alignstats": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/jfarek/alignstats", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "BSD-3-Clause", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/jfarek/alignstats/archive/v0.10.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Comprehensive alignment, whole-genome coverage, and capture coverage statistics.", "tags": null, "text_prefix": false, "timestamp": 1695280893, "version": "0.10" }, "allegro": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://www.nature.com/ng/journal/v37/n10/full/ng1005-1015.html?foxtrotcallback=true", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "INDIVIDUAL", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/BioTools-Tek/packages/raw/master/allegro2/allegro2-2017-10-11.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "A fast linkage and haplotype analysis utility making use of MTBDD to reduce complexity.", "tags": null, "text_prefix": false, "timestamp": 1699528798, "version": "3" }, "amap": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": "https://github.com/mes5k/amap-align", "doc_source_url": null, "doc_url": null, "home": "https://web.archive.org/web/20060902044446/http://bio.math.berkeley.edu/amap/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-2", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/mes5k/amap-align/archive/600fc29fb9d0e8a6abf797c173c7a416ab99c541.zip", "subdirs": [ "linux-aarch64" ], "summary": "AMAP is a multiple sequence alignment program based on sequence annealing.", "tags": null, "text_prefix": false, "timestamp": 1698497200, "version": "2.2" }, "amas": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/marekborowiec/AMAS", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3.0-or-later", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/a/amas/amas-1.0.tar.gz", "subdirs": [ "noarch" ], "summary": "Calculate various summary statistics on a multiple sequence alignment", "tags": null, "text_prefix": false, "timestamp": 1694684044, "version": "1.0" }, "amptk": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": "http://amptk.readthedocs.io/", "home": "https://github.com/nextgenusfs/amptk", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "BSD-2", "post_link": true, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/a/amptk/amptk-1.5.5.tar.gz", "subdirs": [ "noarch" ], "summary": "AMPtk: Amplicon tool kit for processing high throughput amplicon sequencing data.", "tags": null, "text_prefix": true, "timestamp": 1698909929, "version": "1.5.5" }, "angsd": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://www.popgen.dk/angsd/index.php/ANGSD", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPLv3, MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "http://popgen.dk/software/download/angsd/angsd0.940.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "ANGSD: Analysis of next generation Sequencing Data", "tags": null, "text_prefix": false, "timestamp": 1695305964, "version": "0.940" }, "anise_basil": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/seqan/anise_basil", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "BSD", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": null, "subdirs": [ "linux-aarch64" ], "summary": "BASIL is a method to detect breakpoints for structural variants (including insertion breakpoints) from aligned paired HTS reads in BAM format. ANISE is a method for the assembly of large insertions from paired reads in BAM format and a list candidate insert breakpoints as generated by BASIL.", "tags": null, "text_prefix": false, "timestamp": 1697456549, "version": "1.2.0" }, "any2fasta": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/tseemann/any2fasta", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/tseemann/any2fasta/archive/v0.4.2.tar.gz", "subdirs": [ "noarch" ], "summary": "Convert various sequence formats to FASTA", "tags": null, "text_prefix": false, "timestamp": 1694280364, "version": "0.4.2" }, "apoc": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, 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"http://www.ansikte.se/ARAGORN/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPLv3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "http://www.ansikte.se/ARAGORN/Downloads/aragorn1.2.41.c", "subdirs": [ "linux-aarch64" ], "summary": "ARAGORN, tRNA (and tmRNA) detection", "tags": null, "text_prefix": false, "timestamp": 1694282606, "version": "1.2.41" }, "arcs": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/bcgsc/arcs", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/bcgsc/arcs/releases/download/v1.2.5/arcs-1.2.5.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Scaffolding genome sequence assemblies using linked or long reads", "tags": null, "text_prefix": true, "timestamp": 1696936838, "version": "1.2.5" }, "arem": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://cbcl.ics.uci.edu/AREM", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic License", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.python.org/packages/bc/0d/6db36d917d821d150f37c68839d8911e52b78c867b27372da5be41d4cc4f/AREM-1.0.1.tar.gz", "subdirs": [ "noarch" ], "summary": "Aligning Reads by Expectation-Maximization.\\nBased on MACS (Model Based Analysis for ChIP-Seq data)", "tags": null, 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It supports HTTP/HTTPS, FTP, SFTP, BitTorrent and Metalink.", "tags": null, "text_prefix": true, "timestamp": 1697684251, "version": "1.36.0" }, "array-as-vcf": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": "https://github.com/LUMC/array-as-vcf", "doc_source_url": null, "doc_url": "https://github.com/LUMC/array-as-vcf", "home": "https://github.com/LUMC/array-as-vcf", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/a/array-as-vcf/array-as-vcf-1.1.0.tar.gz", "subdirs": [ "noarch" ], "summary": "Convert SNP array to VCF", "tags": null, "text_prefix": false, "timestamp": 1694285844, "version": "1.1.0" }, "arriba": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/suhrig/arriba", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "file:///root/anaconda3/envs/kall/conda-bld/src_cache/arriba_v2.4.0.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Fast and accurate gene fusion detection from RNA-Seq data", "tags": null, "text_prefix": false, "timestamp": 1698830782, "version": "2.4.0" }, "artemis": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://sanger-pathogens.github.io/Artemis/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/sanger-pathogens/Artemis/releases/download/v18.2.0/artemis-unix-release-18.2.0.zip", "subdirs": [ "noarch" ], "summary": "A set of Java genome visualization tools including the Artemis genome browser & annotation tool, ACT DNA sequence comparison viewer, DNA Plotter image generation tool and the BamView BAM/CRAM file viewer.", "tags": null, "text_prefix": false, "timestamp": 1695198228, "version": "18.2.0" }, "artic-porechop": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/artic-network/Porechop", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/artic-network/Porechop/archive/v0.3.2pre.tar.gz", 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"doc_source_url": null, "doc_url": null, "home": "http://doc.arvados.org/sdk/cli/index.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Apache v2", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://rubygems.org/downloads/arvados-cli-2.7.0.gem", "subdirs": [ "linux-aarch64" ], "summary": "Command line interface to Arvados, a free and open source platform for big data science", "tags": null, "text_prefix": true, "timestamp": 1699539842, "version": "2.7.0" }, "ascat": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": "https://github.com/Crick-CancerGenomics/ascat", "doc_source_url": null, "doc_url": null, "home": "https://www.crick.ac.uk/research/a-z-researchers/researchers-v-y/peter-van-loo/software/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/Crick-CancerGenomics/ascat/archive/v3.1.1.tar.gz", "subdirs": [ "noarch" ], "summary": "ASCAT is a method to derive copy number profiles of tumour cells, accounting for normal cell admixture and tumour aneuploidy (Figure 1). ASCAT infers tumour purity (the fraction of tumour cells) and ploidy (the amount of DNA per tumour cell, expressed as multiples of haploid genomes) from SNP array or massively parallel sequencing data, and calculates whole-genome allele-specific copy number profiles (the number of copies of both parental alleles for all SNP loci across the genome).", "tags": null, "text_prefix": false, "timestamp": 1695200230, "version": "3.1.1" }, "assembly-scan": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/rpetit3/assembly-scan", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/rpetit3/assembly-scan/archive/v1.0.0.tar.gz", "subdirs": [ "noarch" ], "summary": "Assembly summary statistics in JSON format", "tags": null, "text_prefix": false, "timestamp": 1695201922, "version": "1.0.0" }, "assembly-stats": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/sanger-pathogens/assembly-stats", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/sanger-pathogens/assembly-stats/archive/v1.0.1.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Get assembly statistics from FASTA and FASTQ files", "tags": null, "text_prefix": false, "timestamp": 1694293319, "version": "1.0.1" }, "assemblyutility": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/yechengxi/AssemblyUtility", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/yechengxi/AssemblyUtility/archive/8e476764eb67ebb486e673ecbd8a0fa5d8eae22c.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Tools for DBG2OLC genoome assembler", "tags": null, "text_prefix": false, "timestamp": 1694293831, "version": "20160209" }, "atac": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://kmer.sourceforge.net/wiki/index.php/Overview_of_the_ATAC_process", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "http://sourceforge.net/projects/kmer/files/ATAC-r2008.tar.bz2", "subdirs": [ "linux-aarch64" ], "summary": "ATAC is a computational process for comparative mapping between two genome assemblies, or between two different genomes", "tags": null, "text_prefix": true, "timestamp": 1700733481, "version": "2008" }, "atactk": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://theparkerlab.org/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3.0-or-later", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/ParkerLab/atactk/archive/0.1.9.tar.gz", "subdirs": [ "noarch" ], "summary": "A toolkit for working with ATAC-seq data.", "tags": null, "text_prefix": true, "timestamp": 1695352039, "version": "0.1.9" }, "ataqv": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": null, "dev_url": "https://github.com/ParkerLab/ataqv", "doc_source_url": null, "doc_url": "https://github.com/ParkerLab/ataqv/blob/master/README.rst", "home": "https://parkerlab.github.io/ataqv/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/ParkerLab/ataqv/archive/1.3.1.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "ataqv is a toolkit for measuring and comparing ATAC-seq results. It was written to help understand how well ATAC-seq assays have worked, and to make it easier to spot differences that might be caused by library prep or sequencing.", "tags": null, "text_prefix": false, "timestamp": 1695350752, "version": "1.3.1" }, "atlas-data-import": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/ebi-gene-expression-group/atlas-data-import", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/ebi-gene-expression-group/atlas-data-import/archive/0.1.1.tar.gz", "subdirs": [ "noarch" ], "summary": "Scripts for extracting expression- and metadata from Single Cell Expression Atlas in a programmatic way.", "tags": null, "text_prefix": true, "timestamp": 1695204350, "version": "0.1.1" }, "atlas-metadata-validator": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "This is a python module to parse a set of MAGE-TAB files and check for compatibility with the Expression Atlas and Single Cell Expression Atlas analysis pipelines. The main validation script automatically detects the experiment type from the MAGE-TAB and runs the respective tests. Currently general checks (for bulk and single-cell experiment) as well as Single Cell Expression Atlas specific checks are supported.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/ebi-gene-expression-group/atlas-metadata-validator", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Apache Software", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/a/atlas-metadata-validator/atlas-metadata-validator-1.6.1.tar.gz", "subdirs": [ "noarch" ], "summary": "A MAGE-TAB validator for Expression Atlas and Single Cell Expression Atlas", "tags": null, "text_prefix": true, "timestamp": 1694297668, "version": "1.6.1" }, "atropos": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://atropos.readthedocs.io/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "CC0 and partly MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/a/atropos/atropos-1.1.31.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "trim adapters from high-throughput sequencing reads", "tags": null, "text_prefix": true, "timestamp": 1694298695, "version": "1.1.31" }, "augustus": { "activate.d": true, "binary_prefix": true, "deactivate.d": true, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://bioinf.uni-greifswald.de/augustus/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic Licence", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/Gaius-Augustus/Augustus/archive/v3.3.3.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "AUGUSTUS is a gene prediction program for eukaryotes written by Mario Stanke and Oliver Keller. It can be used as an ab initio program, which means it bases its prediction purely on the sequence. AUGUSTUS may also incorporate hints on the gene structure coming from extrinsic sources such as EST, MS/MS, protein alignments and synthenic genomic alignments.", "tags": null, "text_prefix": true, "timestamp": 1701137387, "version": "3.3.3" }, "autodock": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://autodock.scripps.edu/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-2.0-only", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://autodock.scripps.edu/wp-content/uploads/sites/56/2021/10/autodocksuite-4.2.6-src.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "AutoDock is a suite of automated docking tools.", "tags": null, "text_prefix": false, "timestamp": 1694301791, "version": "4.2.6" }, "autogrid": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://autodock.scripps.edu/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-2.0-only", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://autodock.scripps.edu/wp-content/uploads/sites/56/2021/10/autodocksuite-4.2.6-src.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "AutoDock is a suite of automated docking tools.", "tags": null, "text_prefix": false, "timestamp": 1694302694, "version": "4.2.6" }, "axe-demultiplexer": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/kdmurray91/axe", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/kdmurray91/axe/archive/0.3.3.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Rapid competitive read demulitplexer. Made with tries.", "tags": null, "text_prefix": false, "timestamp": 1697545106, "version": "0.3.3" }, "axiome": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/neufeld/AXIOME2", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT License", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.python.org/packages/24/10/f8e819957de18eb18fe5197af72ecad3372a562b59e49de7d2ec70b2fe76/axiome-2.0.4.tar.gz", "subdirs": [ "noarch" ], "summary": "AXIOME2: Automation Extension and Integration of Microbial Ecology", "tags": null, "text_prefix": false, "timestamp": 1695695315, "version": "2.0.4" }, "bactopia": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": "https://github.com/bactopia/bactopia/", "doc_source_url": null, "doc_url": null, "home": "https://bactopia.github.io/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": { "3.0.0": { "weak": [ "bactopia >=3.0.0,<3.1.0a0" ] } }, "source_git_url": null, "source_url": "https://github.com/bactopia/bactopia/archive/v3.0.0.tar.gz", "subdirs": [ "noarch" ], "summary": "Bactopia is a flexible pipeline for complete analysis of bacterial genomes.", "tags": null, "text_prefix": false, "timestamp": 1695694618, "version": "3.0.0" }, "baitfisher": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/cmayer/BaitFisher-package", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/cmayer/BaitFisher-package/archive/v1.0.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "The BaitFisher-package is a software package for designing hybrid enrichment probes.", "tags": null, "text_prefix": false, "timestamp": 1694304445, "version": "1.0" }, "bam-readcount": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/genome/bam-readcount", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/genome/bam-readcount/archive/v0.8.0.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "bam-readcount generates metrics at single nucleotide positions.", "tags": null, "text_prefix": true, "timestamp": 1697788983, "version": "0.8" }, "bam2fastq": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/jts/bam2fastq", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "View license", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": null, "subdirs": [ "linux-aarch64" ], "summary": "bam2fastq is a program to extract sequences and qualities from a BAM file.", "tags": null, "text_prefix": false, "timestamp": 1699516456, "version": "1.1.0" }, "bambamc": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/gt1/bambamc", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPLv3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/gt1/bambamc/archive/0.0.50-release-20140430085950.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "lightweight C implementation of name collating BAM file input and BAM file output", "tags": null, "text_prefix": true, "timestamp": 1694306761, "version": "0.0.50" }, "bamclipper": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/tommyau/bamclipper", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/tommyau/bamclipper/archive/v1.0.0.tar.gz", "subdirs": [ "noarch" ], "summary": "Remove primer sequence from BAM alignments by soft-clipping.", "tags": null, "text_prefix": true, "timestamp": 1695869445, "version": "1.0.0" }, "bamhash": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/DecodeGenetics/BamHash", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3-0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/DecodeGenetics/BamHash/archive/1c987784929f5c6cf28b9d36d00017380b922c71.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Hash BAM and FASTQ files to verify data integrity", "tags": null, "text_prefix": false, "timestamp": 1694307604, "version": "1.1" }, "bamm": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/Ecogenomics/BamM", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "LGPL-3.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/Ecogenomics/BamM/archive/1.7.3.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Metagenomics-focused BAM file manipulation", "tags": null, "text_prefix": true, "timestamp": 1699493143, "version": "1.7.3" }, "bamread": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://github.com/endrebak/bamread", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/b/bamread/bamread-0.0.16.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Read bam files quickly into dataframes in Python", "tags": null, "text_prefix": false, "timestamp": 1694308449, "version": "0.0.16" }, "bamscale": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "BAMscale is a one-step tool for either 1) quantifying and normalizing the coverage of peaks or 2) generated scaled BigWig files for easy visualization of commonly used DNA-seq capture based methods.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/ncbi/BAMscale", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Public Domain", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": null, "subdirs": [ "linux-aarch64" ], "summary": "BAMscale is a one-step tool for either 1) quantifying and normalizing the coverage of peaks", "tags": null, "text_prefix": false, "timestamp": 1697006784, "version": "0.0.5" }, "bamstats": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/guigolab/bamstats", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "BSD-3-Clause", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": null, "subdirs": [ "linux-aarch64" ], "summary": "A command line tool to compute mapping statistics from a BAM file", "tags": null, "text_prefix": false, "timestamp": 1690286507, "version": "0.3.5" }, "bamtools": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/pezmaster31/bamtools", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/pezmaster31/bamtools/archive/v2.5.2.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "C++ API & command-line toolkit for working with BAM data", "tags": null, "text_prefix": true, "timestamp": 1694311027, "version": "2.5.2" }, "bamutil": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://genome.sph.umich.edu/wiki/BamUtil", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPLv3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": null, "subdirs": [ "linux-aarch64" ], "summary": "Programs that perform operations on SAM/BAM files, all built into a single executable, bam.", "tags": null, "text_prefix": false, "timestamp": 1694312730, "version": "1.0.15" }, "barcode_splitter": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bitbucket.org/princeton_genomics/barcode_splitter", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GNU", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://bitbucket.org/princeton_genomics/barcode_splitter/get/0.18.6.tar.gz", "subdirs": [ "noarch" ], "summary": "Split multiple fastq files by matching barcodes in one or more of the sequence files. Barcodes in the tab-delimited barcodes.txt file are matched against the beginning (or end) of the specified index read(s). By default, barcodes must match exactly, but --mistmatches can be set higher if desired. Compressed input is read (from all files) if the first input file name ends in .gz. Reading of compressed input can be forced with the gzipin option.", "tags": null, "text_prefix": true, "timestamp": 1695713346, "version": "0.18.6" }, "barrnap": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/tseemann/barrnap", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPLv3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/tseemann/barrnap/archive/0.9.tar.gz", "subdirs": [ "noarch" ], "summary": "Barrnap predicts the location of ribosomal RNA genes in genomes. (bacteria, archaea, metazoan mitochondria and eukaryotes.)", "tags": null, "text_prefix": false, "timestamp": 1695714335, "version": "0.9" }, "barrnap-python": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Original Perl code can be found at the projects homepage here: https://github.com/tseemann/barrnap", "dev_url": "https://github.com/nickp60/barrnap-python", "doc_source_url": null, "doc_url": null, "home": "https://github.com/nickp60/barrnap-python", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GNU General Public License v3.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/b/barrnap/barrnap-0.0.5.tar.gz", "subdirs": [ "noarch" ], "summary": "python package for Torsten Seemann's barrnap package for annotating rRNAs", "tags": null, "text_prefix": true, "timestamp": 1695716085, "version": "0.0.5" }, "bayestyper": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/bioinformatics-centre/BayesTyper", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/bioinformatics-centre/BayesTyper/archive/v1.5.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "A method for variant graph genotyping based on exact alignment of k-mers", "tags": null, "text_prefix": false, "timestamp": 1697611839, "version": "1.5" }, "bazam": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/ssadedin/bazam", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "LGPL v2.1", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/ssadedin/bazam/releases/download/1.0.1/bazam.jar", "subdirs": [ "noarch" ], "summary": "A tool to extract paired reads in FASTQ format from coordinate sorted BAM files", "tags": null, "text_prefix": false, "timestamp": 1694319603, "version": "1.0.1" }, "bcalm": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/GATB/bcalm", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT License", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/GATB/bcalm/archive/v2.2.3.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "BCALM 2 is a bioinformatics tool for constructing the compacted de Bruijn graph from sequencing data.", "tags": null, "text_prefix": true, "timestamp": 1695718031, "version": "2.2.3" }, "bcbio-prioritize": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/chapmanb/bcbio.prioritize", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/chapmanb/bcbio.prioritize/releases/download/v0.0.8/bcbio-prioritize", "subdirs": [ "noarch" ], "summary": "Prioritize small variants, structural variants and coverage based on biological inputs", "tags": null, "text_prefix": false, "timestamp": 1695720481, "version": "0.0.8" }, "bcbio-variation-recall": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/chapmanb/bcbio.variation.recall", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/chapmanb/bcbio.variation.recall/releases/download/v0.2.6/bcbio-variation-recall", "subdirs": [ "noarch" ], "summary": "Parallel merging, squaring off and ensemble calling for genomic variants", "tags": null, "text_prefix": false, "timestamp": 1694326299, "version": "0.2.6" }, "bcftools": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/samtools/bcftools", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/samtools/bcftools/releases/download/1.17/bcftools-1.17.tar.bz2", "subdirs": [ "linux-aarch64" ], "summary": "BCFtools is a set of utilities that manipulate variant calls in the Variant Call Format (VCF) and its binary counterpart BCF. All commands work transparently with both VCFs and BCFs, both uncompressed and BGZF-compressed. Most commands accept VCF, bgzipped VCF and BCF with filetype detected automatically even when streaming from a pipe. Indexed VCF and BCF will work in all situations. Un-indexed VCF and BCF and streams will work in most, but not all situations.", "tags": null, "text_prefix": false, "timestamp": 1696995471, "version": "1.17" }, "bcftools-gtc2vcf-plugin": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/freeseek/gtc2vcf", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": null, "subdirs": [ "linux-aarch64" ], "summary": "Tools to convert Illumina and Affymetrix array intensity data files into VCF files.", "tags": null, "text_prefix": false, "timestamp": 1695801136, "version": "1.16" }, "bcftools-snvphyl-plugin": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/phac-nml/snvphyl-tools", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Apache-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": null, "subdirs": [ "linux-aarch64" ], "summary": "The SNVPhyl (Single Nucleotide Variant PHYLogenomics) pipeline is a pipeline for identifying Single Nucleotide Variants (SNV) within a collection\\ of microbial genomes and constructing a phylogenetic tree. 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Virtual fragment libraries can be created for any BSGenome package, and filter functions for both reads and fragments and basic quality controls are included. Fragment data in the vicinity of the experiment's viewpoint can be visualized as a coverage plot based on a running median approach and a multi-scale contact profile.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/Basic4Cseq.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "LGPL-3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/Basic4Cseq_1.36.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/Basic4Cseq/Basic4Cseq_1.36.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Basic4Cseq_1.36.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-basic4cseq/bioconductor-basic4cseq_1.36.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Basic4Cseq: an R/Bioconductor package for analyzing 4C-seq data", "tags": null, "text_prefix": false, "timestamp": 1693428218, "version": "1.36.0" }, "bioconductor-batchelor": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Implements a variety of methods for batch correction of single-cell (RNA sequencing) data. This includes methods based on detecting mutually nearest neighbors, as well as several efficient variants of linear regression of the log-expression values. Functions are also provided to perform global rescaling to remove differences in depth between batches, and to perform a principal components analysis that is robust to differences in the numbers of cells across batches.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/batchelor.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/batchelor_1.16.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/batchelor/batchelor_1.16.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/batchelor_1.16.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-batchelor/bioconductor-batchelor_1.16.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Single-Cell Batch Correction Methods", "tags": null, "text_prefix": false, "timestamp": 1692939546, "version": "1.16.0" }, "bioconductor-bcrank": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Functions and classes for de novo prediction of transcription factor binding consensus by heuristic search", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/BCRANK.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-2", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/BCRANK_1.62.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/BCRANK/BCRANK_1.62.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/BCRANK_1.62.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-bcrank/bioconductor-bcrank_1.62.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Predicting binding site consensus from ranked DNA sequences", "tags": null, "text_prefix": false, "timestamp": 1691917358, "version": "1.62.0" }, "bioconductor-bcseq": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "This Rcpp-based package implements a highly efficient data structure and algorithm for performing alignment of short reads from CRISPR or shRNA screens to reference barcode library. Sequencing error are considered and matching qualities are evaluated based on Phred scores. A Bayes' classifier is employed to predict the originating barcode of a read. The package supports provision of user-defined probability models for evaluating matching qualities. The package also supports multi-threading.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/bcSeq.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>= 2)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/bcSeq_1.22.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/bcSeq/bcSeq_1.22.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/bcSeq_1.22.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-bcseq/bioconductor-bcseq_1.22.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Fast Sequence Mapping in High-Throughput shRNA and CRISPR Screens", "tags": null, "text_prefix": false, "timestamp": 1692050533, "version": "1.22.0" }, "bioconductor-bdmmacorrect": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Metagenomic sequencing techniques enable quantitative analyses of the microbiome. 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The core function is based on latent factor models and can also be used to predict missing values in any other matrix containing real numbers.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/BEclear.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/BEclear_2.16.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/BEclear/BEclear_2.16.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/BEclear_2.16.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-beclear/bioconductor-beclear_2.16.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Correction of batch effects in DNA methylation data", "tags": null, "text_prefix": false, "timestamp": 1691706295, "version": "2.16.0" }, "bioconductor-bigmelon": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Methods for working with Illumina arrays using gdsfmt.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/bigmelon.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/bigmelon_1.26.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/bigmelon/bigmelon_1.26.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/bigmelon_1.26.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-bigmelon/bioconductor-bigmelon_1.26.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Illumina methylation array analysis for large experiments", "tags": null, "text_prefix": false, "timestamp": 1693540198, "version": "1.26.0" }, "bioconductor-biobase": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Functions that are needed by many other packages or which replace R functions.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/Biobase.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/Biobase_2.60.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/Biobase/Biobase_2.60.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Biobase_2.60.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-biobase/bioconductor-biobase_2.60.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Biobase: Base functions for Bioconductor", "tags": null, "text_prefix": false, "timestamp": 1691418242, "version": "2.60.0" }, "bioconductor-biobtreer": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The biobtreeR package provides an interface to [biobtree](https://github.com/tamerh/biobtree) tool which covers large set of bioinformatics datasets and allows search and chain mappings functionalities.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/biobtreeR.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT + file LICENSE", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/biobtreeR_1.12.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/biobtreeR/biobtreeR_1.12.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/biobtreeR_1.12.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-biobtreer/bioconductor-biobtreer_1.12.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Using biobtree tool from R", "tags": null, "text_prefix": false, "timestamp": 1691116878, "version": "1.12.0" }, "bioconductor-biocbaseutils": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The package provides utility functions related to package development. These include functions that replace slots, and selectors for show methods. It aims to coalesce the various helper functions often re-used throughout the Bioconductor ecosystem.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/BiocBaseUtils.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/BiocBaseUtils_1.2.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/BiocBaseUtils/BiocBaseUtils_1.2.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/BiocBaseUtils_1.2.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-biocbaseutils/bioconductor-biocbaseutils_1.2.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "General utility functions for developing Bioconductor packages", "tags": null, "text_prefix": false, "timestamp": 1691156229, "version": "1.2.0" }, "bioconductor-biocfilecache": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "This package creates a persistent on-disk cache of files that the user can add, update, and retrieve. It is useful for managing resources (such as custom Txdb objects) that are costly or difficult to create, web resources, and data files used across sessions.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/BiocFileCache.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/BiocFileCache_2.8.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/BiocFileCache/BiocFileCache_2.8.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/BiocFileCache_2.8.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-biocfilecache/bioconductor-biocfilecache_2.8.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Manage Files Across Sessions", "tags": null, "text_prefix": false, "timestamp": 1693547657, "version": "2.8.0" }, "bioconductor-biocgenerics": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The package defines many S4 generic functions used in Bioconductor.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/BiocGenerics.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/BiocGenerics_0.46.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/BiocGenerics/BiocGenerics_0.46.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/BiocGenerics_0.46.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-biocgenerics/bioconductor-biocgenerics_0.46.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "S4 generic functions used in Bioconductor", "tags": null, "text_prefix": false, "timestamp": 1693543059, "version": "0.46.0" }, "bioconductor-biocio": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The `BiocIO` package contains high-level abstract classes and generics used by developers to build IO funcionality within the Bioconductor suite of packages. Implements `import()` and `export()` standard generics for importing and exporting biological data formats. `import()` supports whole-file as well as chunk-wise iterative import. The `import()` interface optionally provides a standard mechanism for 'lazy' access via `filter()` (on row or element-like components of the file resource), `select()` (on column-like components of the file resource) and `collect()`. The `import()` interface optionally provides transparent access to remote (e.g. via https) as well as local access. 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The comparison can be used to infer cooperative regulation and thus can be used to generate hypotheses. Several visualization functions are implemented to summarize the coverage of the peak experiment, average profile and heatmap of peaks binding to TSS regions, genomic annotation, distance to TSS, and overlap of peaks or genes.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/ChIPseeker.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/ChIPseeker_1.36.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/ChIPseeker/ChIPseeker_1.36.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/ChIPseeker_1.36.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-chipseeker/bioconductor-chipseeker_1.36.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "ChIPseeker for ChIP peak Annotation, Comparison, and Visualization", "tags": null, "text_prefix": false, "timestamp": 1693489430, "version": "1.36.0" }, "bioconductor-chipseq": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Tools for helping process short read data for chipseq experiments.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/chipseq.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/chipseq_1.50.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/chipseq/chipseq_1.50.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/chipseq_1.50.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-chipseq/bioconductor-chipseq_1.50.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "chipseq: A package for analyzing chipseq data", "tags": null, "text_prefix": false, "timestamp": 1693316430, "version": "1.50.0" }, "bioconductor-chipseqdbdata": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Sorted and indexed BAM files for ChIP-seq libraries, for use in the chipseqDB workflow. 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The trained parameters can be interpreted to infer the clonal structure of the tumor.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/Clomial.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>= 2)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/Clomial_1.36.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/Clomial/Clomial_1.36.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Clomial_1.36.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-clomial/bioconductor-clomial_1.36.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Infers clonal composition of a tumor", "tags": null, "text_prefix": false, "timestamp": 1691158168, "version": "1.36.0" }, "bioconductor-clst": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Package for modified nearest-neighbor classification based on calculation of a similarity threshold distinguishing within-group from between-group comparisons.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/clst.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/clst_1.48.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/clst/clst_1.48.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/clst_1.48.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-clst/bioconductor-clst_1.48.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Classification by local similarity threshold", "tags": null, "text_prefix": false, "timestamp": 1691667383, "version": "1.48.0" }, "bioconductor-clstutils": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Tools for performing taxonomic assignment based on phylogeny using pplacer and clst.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/clstutils.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/clstutils_1.48.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/clstutils/clstutils_1.48.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/clstutils_1.48.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-clstutils/bioconductor-clstutils_1.48.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Tools for performing taxonomic assignment", "tags": null, "text_prefix": false, "timestamp": 1691728290, "version": "1.48.0" }, "bioconductor-clustcomp": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "clustComp is a package that implements several techniques for the comparison and visualisation of relationships between different clustering results, either flat versus flat or hierarchical versus flat. 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The article is called \"Judging the Quality of Gene Expression-Based Clustering Methods Using Gene Annotation\" and it appeared in Genome Research, vol. 12, pp1574-1581 (2002). See package?ClusterJudge for an overview.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/ClusterJudge.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/ClusterJudge_1.22.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/ClusterJudge/ClusterJudge_1.22.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/ClusterJudge_1.22.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-clusterjudge/bioconductor-clusterjudge_1.22.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Judging Quality of Clustering Methods using Mutual Information", "tags": null, "text_prefix": false, "timestamp": 1691693748, "version": "1.22.0" }, "bioconductor-clusterprofiler": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "This package supports functional characteristics of both coding and non-coding genomics data for thousands of species with up-to-date gene annotation. It provides a univeral interface for gene functional annotation from a variety of sources and thus can be applied in diverse scenarios. It provides a tidy interface to access, manipulate, and visualize enrichment results to help users achieve efficient data interpretation. 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Using a Bayesian approach, cn.mops decomposes read variations across samples into integer copy numbers and noise by its mixture components and Poisson distributions, respectively. cn.mops guarantees a low FDR because wrong detections are indicated by high noise and filtered out. cn.mops is very fast and written in C++.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/cn.mops.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "LGPL (>= 2.0)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/cn.mops_1.46.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/cn.mops/cn.mops_1.46.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/cn.mops_1.46.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-cn.mops/bioconductor-cn.mops_1.46.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "cn.mops - Mixture of Poissons for CNV detection in NGS data", "tags": null, "text_prefix": false, "timestamp": 1693541293, "version": "1.46.0" }, "bioconductor-cnanorm": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Performs ratio, GC content correction and normalization of data obtained using low coverage (one read every 100-10,000 bp) high troughput sequencing. 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Our approach uses a non-parametric bootstrap subsampling of the available reference samples to estimate the distribution of read counts from targeted sequencing. As inspired by random forest, this is combined with a procedure that subsamples the amplicons associated with each of the targeted genes. 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However, Limma assumes same prior variance for all genes. In proteomics, the accuracy of protein abundance estimates varies by the number of peptides/PSMs quantified in both label-free and labelled data. Proteins quantification by multiple peptides or PSMs are more accurate. DEqMS package is able to estimate different prior variances for proteins quantified by different number of PSMs/peptides, therefore acchieving better accuracy. 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It defines and detects 3 types of differentially expressed genes between two groups of single cells, with regard to different expression status (DEs), differential expression abundance (DEa), and general differential expression (DEg). DEsingle employs Zero-Inflated Negative Binomial model to estimate the proportion of real and dropout zeros and to define and detect the 3 types of DE genes. 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These funtions and data are also useful for gene set analysis using other methods.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/gage.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>=2.0)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/gage_2.50.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/gage/gage_2.50.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/gage_2.50.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gage/bioconductor-gage_2.50.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Generally Applicable Gene-set Enrichment for Pathway Analysis", "tags": null, "text_prefix": false, "timestamp": 1692641188, "version": "2.50.0" }, "bioconductor-garfield": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "GARFIELD is a non-parametric functional enrichment analysis approach described in the paper GARFIELD: GWAS analysis of regulatory or functional information enrichment with LD correction. 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Next, it quantifies Fold Enrichment (FE) at various GWAS significance cutoffs and assesses them by permutation testing, while matching for minor allele frequency, distance to nearest transcription start site and number of LD proxies (r2 > 0.8).", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/garfield.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/garfield_1.28.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/garfield/garfield_1.28.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/garfield_1.28.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-garfield/bioconductor-garfield_1.28.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "GWAS Analysis of Regulatory or Functional Information Enrichment with LD correction", "tags": null, "text_prefix": false, "timestamp": 1691133406, "version": "1.28.0" }, "bioconductor-gars": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Feature selection aims to identify and remove redundant, irrelevant and noisy variables from high-dimensional datasets. Selecting informative features affects the subsequent classification and regression analyses by improving their overall performances. Several methods have been proposed to perform feature selection: most of them relies on univariate statistics, correlation, entropy measurements or the usage of backward/forward regressions. Herein, we propose an efficient, robust and fast method that adopts stochastic optimization approaches for high-dimensional. GARS is an innovative implementation of a genetic algorithm that selects robust features in high-dimensional and challenging datasets.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/GARS.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>= 2)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/GARS_1.20.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/GARS/GARS_1.20.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/GARS_1.20.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gars/bioconductor-gars_1.20.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "GARS: Genetic Algorithm for the identification of Robust Subsets of variables in high-dimensional and challenging datasets", "tags": null, "text_prefix": false, "timestamp": 1694029253, "version": "1.20.0" }, "bioconductor-gcrisprtools": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Set of tools for evaluating pooled high-throughput screening experiments, typically employing CRISPR/Cas9 or shRNA expression cassettes. Contains methods for interrogating library and cassette behavior within an experiment, identifying differentially abundant cassettes, aggregating signals to identify candidate targets for empirical validation, hypothesis testing, and comprehensive reporting. Version 2.0 extends these applications to include a variety of tools for contextualizing and integrating signals across many experiments, incorporates extended signal enrichment methodologies via the \"sparrow\" package, and streamlines many formal requirements to aid in interpretablity.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/gCrisprTools.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/gCrisprTools_2.6.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/gCrisprTools/gCrisprTools_2.6.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/gCrisprTools_2.6.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gcrisprtools/bioconductor-gcrisprtools_2.6.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Suite of Functions for Pooled Crispr Screen QC and Analysis", "tags": null, "text_prefix": false, "timestamp": 1692226008, "version": "2.6.0" }, "bioconductor-gcspikelite": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Spike-in data for GC/MS data and methods within flagme", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/data/experiment/html/gcspikelite.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "LGPL", "post_link": true, "pre_link": false, "pre_unlink": true, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/gcspikelite_1.38.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/gcspikelite/gcspikelite_1.38.0.tar.gz", "https://bioconductor.org/packages/3.17/data/experiment/src/contrib/gcspikelite_1.38.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gcspikelite/bioconductor-gcspikelite_1.38.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Spike-in data for GC/MS data and methods within flagme", "tags": null, "text_prefix": false, "timestamp": 1691537958, "version": "1.38.0" }, "bioconductor-gcsscore": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "For differential expression analysis of 3'IVT and WT-style microarrays from Affymetrix/Thermo-Fisher. Based on S-score algorithm originally described by Zhang et al 2002.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/GCSscore.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>=3)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/GCSscore_1.14.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/GCSscore/GCSscore_1.14.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/GCSscore_1.14.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gcsscore/bioconductor-gcsscore_1.14.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "GCSscore: an R package for microarray analysis for Affymetrix/Thermo Fisher arrays", "tags": null, "text_prefix": false, "timestamp": 1692323506, "version": "1.14.0" }, "bioconductor-gdcrnatools": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "This is an easy-to-use package for downloading, organizing, and integrative analyzing RNA expression data in GDC with an emphasis on deciphering the lncRNA-mRNA related ceRNA regulatory network in cancer. Three databases of lncRNA-miRNA interactions including spongeScan, starBase, and miRcode, as well as three databases of mRNA-miRNA interactions including miRTarBase, starBase, and miRcode are incorporated into the package for ceRNAs network construction. limma, edgeR, and DESeq2 can be used to identify differentially expressed genes/miRNAs. Functional enrichment analyses including GO, KEGG, and DO can be performed based on the clusterProfiler and DO packages. Both univariate CoxPH and KM survival analyses of multiple genes can be implemented in the package. Besides some routine visualization functions such as volcano plot, bar plot, and KM plot, a few simply shiny apps are developed to facilitate visualization of results on a local webpage.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/GDCRNATools.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/GDCRNATools_1.20.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/GDCRNATools/GDCRNATools_1.20.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/GDCRNATools_1.20.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gdcrnatools/bioconductor-gdcrnatools_1.20.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "GDCRNATools: an R/Bioconductor package for integrative analysis of lncRNA, mRNA, and miRNA data in GDC", "tags": null, "text_prefix": false, "timestamp": 1694036459, "version": "1.20.0" }, "bioconductor-gdsarray": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "GDS files are widely used to represent genotyping or sequence data. The GDSArray package implements the `GDSArray` class to represent nodes in GDS files in a matrix-like representation that allows easy manipulation (e.g., subsetting, mathematical transformation) in _R_. The data remains on disk until needed, so that very large files can be processed.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/GDSArray.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/GDSArray_1.20.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/GDSArray/GDSArray_1.20.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/GDSArray_1.20.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gdsarray/bioconductor-gdsarray_1.20.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Representing GDS files as array-like objects", "tags": null, "text_prefix": false, "timestamp": 1692143200, "version": "1.20.0" }, "bioconductor-gdsfmt": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Provides a high-level R interface to CoreArray Genomic Data Structure (GDS) data files. GDS is portable across platforms with hierarchical structure to store multiple scalable array-oriented data sets with metadata information. It is suited for large-scale datasets, especially for data which are much larger than the available random-access memory. The gdsfmt package offers the efficient operations specifically designed for integers of less than 8 bits, since a diploid genotype, like single-nucleotide polymorphism (SNP), usually occupies fewer bits than a byte. Data compression and decompression are available with relatively efficient random access. It is also allowed to read a GDS file in parallel with multiple R processes supported by the package parallel.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/gdsfmt.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "LGPL-3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/gdsfmt_1.36.1.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/gdsfmt/gdsfmt_1.36.1.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/gdsfmt_1.36.1.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gdsfmt/bioconductor-gdsfmt_1.36.1_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "R Interface to CoreArray Genomic Data Structure (GDS) Files", "tags": null, "text_prefix": false, "timestamp": 1692270138, "version": "1.36.1" }, "bioconductor-gem": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Tools for analyzing EWAS, methQTL and GxE genome widely.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/GEM.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/GEM_1.26.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/GEM/GEM_1.26.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/GEM_1.26.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gem/bioconductor-gem_1.26.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "GEM: fast association study for the interplay of Gene, Environment and Methylation", "tags": null, "text_prefix": false, "timestamp": 1691304905, "version": "1.26.0" }, "bioconductor-gemini": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "GEMINI uses log-fold changes to model sample-dependent and independent effects, and uses a variational Bayes approach to infer these effects. The inferred effects are used to score and identify genetic interactions, such as lethality and recovery. More details can be found in Zamanighomi et al. 2019 (in press).", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/gemini.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "BSD_3_clause + file LICENSE", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/gemini_1.14.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/gemini/gemini_1.14.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/gemini_1.14.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gemini/bioconductor-gemini_1.14.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "GEMINI: Variational inference approach to infer genetic interactions from pairwise CRISPR screens", "tags": null, "text_prefix": false, "timestamp": 1691656105, "version": "1.14.0" }, "bioconductor-genarise": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "genArise is an easy to use tool for dual color microarray data. Its GUI-Tk based environment let any non-experienced user performs a basic, but not simple, data analysis just following a wizard. In addition it provides some tools for the developer.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/genArise.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "file LICENSE", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/genArise_1.76.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/genArise/genArise_1.76.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/genArise_1.76.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-genarise/bioconductor-genarise_1.76.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Microarray Analysis tool", "tags": null, "text_prefix": false, "timestamp": 1691524122, "version": "1.76.0" }, "bioconductor-genbankr": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Reads Genbank files.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/genbankr.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/genbankr_1.27.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/genbankr/genbankr_1.27.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/genbankr_1.27.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-genbankr/bioconductor-genbankr_1.27.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Parsing GenBank files into semantically useful objects", "tags": null, "text_prefix": false, "timestamp": 1693458591, "version": "1.27.0" }, "bioconductor-geneattribution": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Identification of the most likely gene or genes through which variation at a given genomic locus in the human genome acts. The most basic functionality assumes that the closer gene is to the input locus, the more likely the gene is to be causative. 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The phenotype of each siRNA is modeled based on on-targeted and off-targeted genes, using a regularized linear regression model.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/gespeR.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/gespeR_1.31.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/gespeR/gespeR_1.31.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/gespeR_1.31.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gesper/bioconductor-gesper_1.31.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Gene-Specific Phenotype EstimatoR", "tags": null, "text_prefix": false, "timestamp": 1693490543, "version": "1.31.0" }, "bioconductor-ggbio": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The ggbio package extends and specializes the grammar of graphics for biological data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor data structures are supported, where appropriate. The package supports detailed views of particular genomic regions, as well as genome-wide overviews. Supported overviews include ideograms and grand linear views. High-level plots include sequence fragment length, edge-linked interval to data view, mismatch pileup, and several splicing summaries.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/ggbio.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/ggbio_1.48.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/ggbio/ggbio_1.48.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/ggbio_1.48.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-ggbio/bioconductor-ggbio_1.48.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Visualization tools for genomic data", "tags": null, "text_prefix": false, "timestamp": 1693474667, "version": "1.48.0" }, "bioconductor-ggtree": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "'ggtree' extends the 'ggplot2' plotting system which implemented the grammar of graphics. 'ggtree' is designed for visualization and annotation of phylogenetic trees and other tree-like structures with their annotation data.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/ggtree.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/ggtree_3.8.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/ggtree/ggtree_3.8.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/ggtree_3.8.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-ggtree/bioconductor-ggtree_3.8.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "an R package for visualization of tree and annotation data", "tags": null, "text_prefix": false, "timestamp": 1691670973, "version": "3.8.0" }, "bioconductor-gigsea": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "We presented the Genotype-imputed Gene Set Enrichment Analysis (GIGSEA), a novel method that uses GWAS-and-eQTL-imputed trait-associated differential gene expression to interrogate gene set enrichment for the trait-associated SNPs. By incorporating eQTL from large gene expression studies, e.g. GTEx, GIGSEA appropriately addresses such challenges for SNP enrichment as gene size, gene boundary, SNP distal regulation, and multiple-marker regulation. The weighted linear regression model, taking as weights both imputation accuracy and model completeness, was used to perform the enrichment test, properly adjusting the bias due to redundancy in different gene sets. The permutation test, furthermore, is used to evaluate the significance of enrichment, whose efficiency can be largely elevated by expressing the computational intensive part in terms of large matrix operation. We have shown the appropriate type I error rates for GIGSEA (<5%), and the preliminary results also demonstrate its good performance to uncover the real signal.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/GIGSEA.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "LGPL-3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/GIGSEA_1.18.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/GIGSEA/GIGSEA_1.18.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/GIGSEA_1.18.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gigsea/bioconductor-gigsea_1.18.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Genotype Imputed Gene Set Enrichment Analysis", "tags": null, "text_prefix": false, "timestamp": 1691381822, "version": "1.18.0" }, "bioconductor-girafe": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The package 'girafe' deals with the genome-level representation of aligned reads from next-generation sequencing data. It contains an object class for enabling a detailed description of genome intervals with aligned reads and functions for comparing, visualising, exporting and working with such intervals and the aligned reads. As such, the package interacts with and provides a link between the packages ShortRead, IRanges and genomeIntervals.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/girafe.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/girafe_1.52.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/girafe/girafe_1.52.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/girafe_1.52.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-girafe/bioconductor-girafe_1.52.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Genome Intervals and Read Alignments for Functional Exploration", "tags": null, "text_prefix": false, "timestamp": 1693297861, "version": "1.52.0" }, "bioconductor-gispa": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "GISPA is a method intended for the researchers who are interested in defining gene sets with similar, a priori specified molecular profile. GISPA method has been previously published in Nucleic Acid Research (Kowalski et al., 2016; PMID: 26826710).", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/GISPA.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-2", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/GISPA_1.24.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/GISPA/GISPA_1.24.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/GISPA_1.24.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gispa/bioconductor-gispa_1.24.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "GISPA: Method for Gene Integrated Set Profile Analysis", "tags": null, "text_prefix": false, "timestamp": 1693414955, "version": "1.24.0" }, "bioconductor-gladiatox": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "GladiaTOX R package is an open-source, flexible solution to high-content screening data processing and reporting in biomedical research. GladiaTOX takes advantage of the tcpl core functionalities and provides a number of extensions: it provides a web-service solution to fetch raw data; it computes severity scores and exports ToxPi formatted files; furthermore it contains a suite of functionalities to generate pdf reports for quality control and data processing.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/GladiaTOX.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-2", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/GladiaTOX_1.16.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/GladiaTOX/GladiaTOX_1.16.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/GladiaTOX_1.16.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gladiatox/bioconductor-gladiatox_1.16.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "R Package for Processing High Content Screening data", "tags": null, "text_prefix": false, "timestamp": 1697682205, "version": "1.16.0" }, "bioconductor-globaltest": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The global test tests groups of covariates (or features) for association with a response variable. This package implements the test with diagnostic plots and multiple testing utilities, along with several functions to facilitate the use of this test for gene set testing of GO and KEGG terms.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/globaltest.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>= 2)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/globaltest_5.54.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/globaltest/globaltest_5.54.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/globaltest_5.54.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-globaltest/bioconductor-globaltest_5.54.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Testing Groups of Covariates/Features for Association with a Response Variable, with Applications to Gene Set Testing", "tags": null, "text_prefix": false, "timestamp": 1692894290, "version": "5.54.0" }, "bioconductor-gmapr": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": "GSNAP and GMAP are a pair of tools to align short-read data written by Tom Wu. This package provides convenience methods to work with GMAP and GSNAP from within R. In addition, it provides methods to tally alignment results on a per-nucleotide basis using the bam_tally tool.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/gmapR.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/gmapR_1.42.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/gmapR/gmapR_1.42.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/gmapR_1.42.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gmapr/bioconductor-gmapr_1.42.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "An R interface to the GMAP/GSNAP/GSTRUCT suite", "tags": null, "text_prefix": false, "timestamp": 1693461324, "version": "1.42.0" }, "bioconductor-gnet2": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Cluster genes to functional groups with E-M process. Iteratively perform TF assigning and Gene assigning, until the assignment of genes did not change, or max number of iterations is reached.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/GNET2.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Apache License 2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/GNET2_1.16.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/GNET2/GNET2_1.16.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/GNET2_1.16.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gnet2/bioconductor-gnet2_1.16.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Constructing gene regulatory networks from expression data through functional module inference", "tags": null, "text_prefix": false, "timestamp": 1698320902, "version": "1.16.0" }, "bioconductor-go.db": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "A set of annotation maps describing the entire Gene Ontology assembled using data from GO", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/data/annotation/html/GO.db.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": true, "pre_link": false, "pre_unlink": true, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/GO.db_3.17.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/GO.db/GO.db_3.17.0.tar.gz", "https://bioconductor.org/packages/3.17/data/annotation/src/contrib/GO.db_3.17.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-go.db/bioconductor-go.db_3.17.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "A set of annotation maps describing the entire Gene Ontology", "tags": null, "text_prefix": false, "timestamp": 1692064160, "version": "3.17.0" }, "bioconductor-goexpress": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The package contains methods to visualise the expression profile of genes from a microarray or RNA-seq experiment, and offers a supervised clustering approach to identify GO terms containing genes with expression levels that best classify two or more predefined groups of samples. Annotations for the genes present in the expression dataset may be obtained from Ensembl through the biomaRt package, if not provided by the user. The default random forest framework is used to evaluate the capacity of each gene to cluster samples according to the factor of interest. Finally, GO terms are scored by averaging the rank (alternatively, score) of their respective gene sets to cluster the samples. P-values may be computed to assess the significance of GO term ranking. Visualisation function include gene expression profile, gene ontology-based heatmaps, and hierarchical clustering of experimental samples using gene expression data.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/GOexpress.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>= 3)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/GOexpress_1.34.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/GOexpress/GOexpress_1.34.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/GOexpress_1.34.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-goexpress/bioconductor-goexpress_1.34.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Visualise microarray and RNAseq data using gene ontology annotations", "tags": null, "text_prefix": false, "timestamp": 1692822476, "version": "1.34.0" }, "bioconductor-gofuncr": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "GOfuncR performs a gene ontology enrichment analysis based on the ontology enrichment software FUNC. GO-annotations are obtained from OrganismDb or OrgDb packages ('Homo.sapiens' by default); the GO-graph is included in the package and updated regularly (01-May-2021). GOfuncR provides the standard candidate vs. background enrichment analysis using the hypergeometric test, as well as three additional tests: (i) the Wilcoxon rank-sum test that is used when genes are ranked, (ii) a binomial test that is used when genes are associated with two counts and (iii) a Chi-square or Fisher's exact test that is used in cases when genes are associated with four counts. To correct for multiple testing and interdependency of the tests, family-wise error rates are computed based on random permutations of the gene-associated variables. GOfuncR also provides tools for exploring the ontology graph and the annotations, and options to take gene-length or spatial clustering of genes into account. It is also possible to provide custom gene coordinates, annotations and ontologies.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/GOfuncR.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>= 2)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/GOfuncR_1.20.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/GOfuncR/GOfuncR_1.20.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/GOfuncR_1.20.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-gofuncr/bioconductor-gofuncr_1.20.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Gene ontology enrichment using FUNC", "tags": null, "text_prefix": false, "timestamp": 1693627628, "version": "1.20.0" }, "bioconductor-goprofiles": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The package implements methods to compare lists of genes based on comparing the corresponding 'functional profiles'.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/goProfiles.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-2", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/goProfiles_1.62.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/goProfiles/goProfiles_1.62.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/goProfiles_1.62.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-goprofiles/bioconductor-goprofiles_1.62.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "goProfiles: an R package for the statistical analysis of functional profiles", "tags": null, "text_prefix": false, "timestamp": 1693168561, "version": "1.62.0" }, "bioconductor-gosemsim": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The semantic comparisons of Gene Ontology (GO) annotations provide quantitative ways to compute similarities between genes and gene groups, and have became important basis for many bioinformatics analysis approaches. GOSemSim is an R package for semantic similarity computation among GO terms, sets of GO terms, gene products and gene clusters. 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MaAsLin2 is the next generation of MaAsLin.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/Maaslin2.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT + file LICENSE", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/Maaslin2_1.14.1.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/Maaslin2/Maaslin2_1.14.1.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Maaslin2_1.14.1.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-maaslin2/bioconductor-maaslin2_1.14.1_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "\"Multivariable Association Discovery in Population-scale Meta-omics Studies\"", "tags": null, "text_prefix": false, "timestamp": 1692442924, "version": "1.14.1" }, "bioconductor-mafdb.exac.r1.0.hs37d5": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Store minor allele frequency data from the Exome Aggregation Consortium (ExAC release 1.0) for the human genome version hs37d5.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/data/annotation/html/MafDb.ExAC.r1.0.hs37d5.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": true, "pre_link": false, "pre_unlink": true, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/MafDb.ExAC.r1.0.hs37d5_3.10.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/MafDb.ExAC.r1.0.hs37d5/MafDb.ExAC.r1.0.hs37d5_3.10.0.tar.gz", "https://bioconductor.org/packages/3.17/data/annotation/src/contrib/MafDb.ExAC.r1.0.hs37d5_3.10.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-mafdb.exac.r1.0.hs37d5/bioconductor-mafdb.exac.r1.0.hs37d5_3.10.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Minor allele frequency data from ExAC release 1.0 for hs37d5", "tags": null, "text_prefix": false, "timestamp": 1692828026, "version": "3.10.0" }, "bioconductor-mafdb.gnomadex.r2.1.hs37d5": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Store minor allele frequency data from the Genome Aggregation Database (gnomAD exomes release 2.1) for the human genome version hs37d5.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/data/annotation/html/MafDb.gnomADex.r2.1.hs37d5.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": true, "pre_link": false, "pre_unlink": true, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/MafDb.gnomADex.r2.1.hs37d5_3.10.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/MafDb.gnomADex.r2.1.hs37d5/MafDb.gnomADex.r2.1.hs37d5_3.10.0.tar.gz", "https://bioconductor.org/packages/3.17/data/annotation/src/contrib/MafDb.gnomADex.r2.1.hs37d5_3.10.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-mafdb.gnomadex.r2.1.hs37d5/bioconductor-mafdb.gnomadex.r2.1.hs37d5_3.10.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Minor allele frequency data from gnomAD exomes release 2.1 for hs37d5", "tags": null, "text_prefix": false, "timestamp": 1692664650, "version": "3.10.0" }, "bioconductor-maftools": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": "Analyze and visualize Mutation Annotation Format (MAF) files from large scale sequencing studies. This package provides various functions to perform most commonly used analyses in cancer genomics and to create feature rich customizable visualzations with minimal effort.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/maftools.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT + file LICENSE", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/maftools_2.16.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/maftools/maftools_2.16.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/maftools_2.16.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-maftools/bioconductor-maftools_2.16.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Summarize, Analyze and Visualize MAF Files", "tags": null, "text_prefix": false, "timestamp": 1691797469, "version": "2.16.0" }, "bioconductor-mageckflute": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "CRISPR (clustered regularly interspaced short palindrome repeats) coupled with nuclease Cas9 (CRISPR/Cas9) screens represent a promising technology to systematically evaluate gene functions. Data analysis for CRISPR/Cas9 screens is a critical process that includes identifying screen hits and exploring biological functions for these hits in downstream analysis. We have previously developed two algorithms, MAGeCK and MAGeCK-VISPR, to analyze CRISPR/Cas9 screen data in various scenarios. These two algorithms allow users to perform quality control, read count generation and normalization, and calculate beta score to evaluate gene selection performance. In downstream analysis, the biological functional analysis is required for understanding biological functions of these identified genes with different screening purposes. Here, We developed MAGeCKFlute for supporting downstream analysis. MAGeCKFlute provides several strategies to remove potential biases within sgRNA-level read counts and gene-level beta scores. The downstream analysis with the package includes identifying essential, non-essential, and target-associated genes, and performing biological functional category analysis, pathway enrichment analysis and protein complex enrichment analysis of these genes. The package also visualizes genes in multiple ways to benefit users exploring screening data. Collectively, MAGeCKFlute enables accurate identification of essential, non-essential, and targeted genes, as well as their related biological functions. This vignette explains the use of the package and demonstrates typical workflows.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/MAGeCKFlute.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>=3)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/MAGeCKFlute_2.4.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/MAGeCKFlute/MAGeCKFlute_2.4.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/MAGeCKFlute_2.4.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-mageckflute/bioconductor-mageckflute_2.4.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Integrative Analysis Pipeline for Pooled CRISPR Functional Genetic Screens", "tags": null, "text_prefix": false, "timestamp": 1693522607, "version": "2.4.0" }, "bioconductor-maigespack": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "This package uses functions of various other packages together with other functions in a coordinated way to handle and analyse cDNA microarray data", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/maigesPack.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>= 2)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/maigesPack_1.64.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/maigesPack/maigesPack_1.64.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/maigesPack_1.64.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-maigespack/bioconductor-maigespack_1.64.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Functions to handle cDNA microarray data, including several methods of data analysis", "tags": null, "text_prefix": false, "timestamp": 1691860147, "version": "1.64.0" }, "bioconductor-mait": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The MAIT package contains functions to perform end-to-end statistical analysis of LC/MS Metabolomic Data. Special emphasis is put on peak annotation and in modular function design of the functions.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/MAIT.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-2", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/MAIT_1.34.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/MAIT/MAIT_1.34.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/MAIT_1.34.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-mait/bioconductor-mait_1.34.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Statistical Analysis of Metabolomic Data", "tags": null, "text_prefix": false, "timestamp": 1694053257, "version": "1.34.0" }, "bioconductor-mantelcorr": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Computes Mantel cluster correlations from a (p x n) numeric data matrix (e.g. microarray gene-expression data).", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/MantelCorr.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>= 2)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/MantelCorr_1.70.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/MantelCorr/MantelCorr_1.70.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/MantelCorr_1.70.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-mantelcorr/bioconductor-mantelcorr_1.70.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Compute Mantel Cluster Correlations", "tags": null, "text_prefix": false, "timestamp": 1691402322, "version": "1.70.0" }, "bioconductor-marray": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Class definitions for two-color spotted microarray data. Fuctions for data input, diagnostic plots, normalization and quality checking.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/marray.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "LGPL", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/marray_1.78.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/marray/marray_1.78.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/marray_1.78.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-marray/bioconductor-marray_1.78.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Exploratory analysis for two-color spotted microarray data", "tags": null, "text_prefix": false, "timestamp": 1691422066, "version": "1.78.0" }, "bioconductor-martini": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "martini deals with the low power inherent to GWAS studies by using prior knowledge represented as a network. SNPs are the vertices of the network, and the edges represent biological relationships between them (genomic adjacency, belonging to the same gene, physical interaction between protein products). The network is scanned using SConES, which looks for groups of SNPs maximally associated with the phenotype, that form a close subnetwork.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/martini.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/martini_1.20.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/martini/martini_1.20.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/martini_1.20.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-martini/bioconductor-martini_1.20.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "GWAS Incorporating Networks", "tags": null, "text_prefix": false, "timestamp": 1691798492, "version": "1.20.0" }, "bioconductor-massarray": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "This package is designed for the import, quality control, analysis, and visualization of methylation data generated using Sequenom's MassArray platform. The tools herein contain a highly detailed amplicon prediction for optimal assay design. Also included are quality control measures of data, such as primer dimer and bisulfite conversion efficiency estimation. Methylation data are calculated using the same algorithms contained in the EpiTyper software package. Additionally, automatic SNP-detection can be used to flag potentially confounded data from specific CG sites. Visualization includes barplots of methylation data as well as UCSC Genome Browser-compatible BED tracks. Multiple assays can be positionally combined for integrated analysis.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/MassArray.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>=2)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/MassArray_1.52.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/MassArray/MassArray_1.52.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/MassArray_1.52.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-massarray/bioconductor-massarray_1.52.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Analytical Tools for MassArray Data", "tags": null, "text_prefix": false, "timestamp": 1691404397, "version": "1.52.0" }, "bioconductor-massir": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Predicts the sex of samples in gene expression microarray datasets", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/massiR.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/massiR_1.36.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/massiR/massiR_1.36.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/massiR_1.36.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-massir/bioconductor-massir_1.36.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "massiR: MicroArray Sample Sex Identifier", "tags": null, "text_prefix": false, "timestamp": 1691800156, "version": "1.36.0" }, "bioconductor-massspecwavelet": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Peak Detection in Mass Spectrometry data is one of the important preprocessing steps. The performance of peak detection affects subsequent processes, including protein identification, profile alignment and biomarker identification. Using Continuous Wavelet Transform (CWT), this package provides a reliable algorithm for peak detection that does not require any type of smoothing or previous baseline correction method, providing more consistent results for different spectra. See = 2)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/MassSpecWavelet_1.66.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/MassSpecWavelet/MassSpecWavelet_1.66.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/MassSpecWavelet_1.66.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-massspecwavelet/bioconductor-massspecwavelet_1.66.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Peak Detection for Mass Spectrometry data using wavelet-based algorithms", "tags": null, "text_prefix": false, "timestamp": 1691280283, "version": "1.66.0" }, "bioconductor-matrixgenerics": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "S4 generic functions modeled after the 'matrixStats' API for alternative matrix implementations. Packages with alternative matrix implementation can depend on this package and implement the generic functions that are defined here for a useful set of row and column summary statistics. 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Methylation calling can be performed directly from Bismark aligned BAM files.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/methylKit.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/methylKit_1.26.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/methylKit/methylKit_1.26.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/methylKit_1.26.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-methylkit/bioconductor-methylkit_1.26.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "DNA methylation analysis from high-throughput bisulfite sequencing results", "tags": null, "text_prefix": false, "timestamp": 1692647094, "version": "1.26.0" }, "bioconductor-methylmix": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "MethylMix is an algorithm implemented to identify hyper and hypomethylated genes for a disease. MethylMix is based on a beta mixture model to identify methylation states and compares them with the normal DNA methylation state. MethylMix uses a novel statistic, the Differential Methylation value or DM-value defined as the difference of a methylation state with the normal methylation state. Finally, matched gene expression data is used to identify, besides differential, functional methylation states by focusing on methylation changes that effect gene expression. References: Gevaert 0. MethylMix: an R package for identifying DNA methylation-driven genes. Bioinformatics (Oxford, England). 2015;31(11):1839-41. doi:10.1093/bioinformatics/btv020. Gevaert O, Tibshirani R, Plevritis SK. Pancancer analysis of DNA methylation-driven genes using MethylMix. Genome Biology. 2015;16(1):17. doi:10.1186/s13059-014-0579-8.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/MethylMix.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-2", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/MethylMix_2.30.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/MethylMix/MethylMix_2.30.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/MethylMix_2.30.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-methylmix/bioconductor-methylmix_2.30.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "MethylMix: Identifying methylation driven cancer genes", "tags": null, "text_prefix": false, "timestamp": 1691547129, "version": "2.30.0" }, "bioconductor-methylmnm": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "To give the exactly p-value and q-value of MeDIP-seq and MRE-seq data for different samples comparation.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/methylMnM.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/methylMnM_1.38.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/methylMnM/methylMnM_1.38.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/methylMnM_1.38.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-methylmnm/bioconductor-methylmnm_1.38.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "detect different methylation level (DMR)", "tags": null, "text_prefix": false, "timestamp": 1691802003, "version": "1.38.0" }, "bioconductor-methylpipe": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Memory efficient analysis of base resolution DNA methylation data in both the CpG and non-CpG sequence context. Integration of DNA methylation data derived from any methodology providing base- or low-resolution data.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/methylPipe.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL(>=2)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/methylPipe_1.34.1.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/methylPipe/methylPipe_1.34.1.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/methylPipe_1.34.1.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-methylpipe/bioconductor-methylpipe_1.34.1_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Base resolution DNA methylation data analysis", "tags": null, "text_prefix": false, "timestamp": 1693516390, "version": "1.34.1" }, "bioconductor-methylseekr": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "This is a package for the discovery of regulatory regions from Bis-seq data", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/MethylSeekR.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>=2)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/MethylSeekR_1.40.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/MethylSeekR/MethylSeekR_1.40.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/MethylSeekR_1.40.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-methylseekr/bioconductor-methylseekr_1.40.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Segmentation of Bis-seq data", "tags": null, "text_prefix": false, "timestamp": 1694015838, "version": "1.40.0" }, "bioconductor-methylsig": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "MethylSig is a package for testing for differentially methylated cytosines (DMCs) or regions (DMRs) in whole-genome bisulfite sequencing (WGBS) or reduced representation bisulfite sequencing (RRBS) experiments. 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Based on eSet, it can contain MIAME information, sample information, feature information, and multiple matrices of data. An \"intelligent\" import function, methylumiR can read the Illumina text files and create a MethyLumiSet. methylumIDAT can directly read raw IDAT files from HumanMethylation27 and HumanMethylation450 microarrays. 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The package mgsa implements MGSA and tools to use MGSA together with the Gene Ontology.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/mgsa.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/mgsa_1.48.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/mgsa/mgsa_1.48.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/mgsa_1.48.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-mgsa/bioconductor-mgsa_1.48.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Model-based gene set analysis", "tags": null, "text_prefix": false, "timestamp": 1691413191, "version": "1.48.0" }, "bioconductor-mgu74av2.db": { "activate.d": 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MIRA aggregates genome-scale DNA methylation data into a DNA methylation profile for a given region set with shared biological annotation. Using this profile, MIRA infers and scores the collective regulatory activity for the region set. 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These data are used by the miRcomp package to assess the performance of methods that estimate expression from the amplification curves.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/data/experiment/html/miRcompData.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3 | file LICENSE", "post_link": true, "pre_link": false, "pre_unlink": true, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/miRcompData_1.30.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/miRcompData/miRcompData_1.30.0.tar.gz", "https://bioconductor.org/packages/3.17/data/experiment/src/contrib/miRcompData_1.30.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-mircompdata/bioconductor-mircompdata_1.30.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Data used in the miRcomp package", "tags": null, "text_prefix": false, "timestamp": 1691552303, "version": "1.30.0" }, "bioconductor-mirnapath": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "This package provides pathway enrichment techniques for miRNA expression data. 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The normalisation procedure is subset-quantile within-array normalisation (SWAN), which allows Infinium I and II type probes on a single array to be normalised together. The test for differential variability is based on an empirical Bayes version of Levene's test. Differential methylation testing is performed using RUV, which can adjust for systematic errors of unknown origin in high-dimensional data by using negative control probes. Gene ontology analysis is performed by taking into account the number of probes per gene on the array, as well as taking into account multi-gene associated probes.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/missMethyl.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-2", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/missMethyl_1.34.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/missMethyl/missMethyl_1.34.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/missMethyl_1.34.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-missmethyl/bioconductor-missmethyl_1.34.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Analysing Illumina HumanMethylation BeadChip Data", "tags": null, "text_prefix": false, "timestamp": 1698458270, "version": "1.34.0" }, "bioconductor-mlseq": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "This package applies several machine learning methods, including SVM, bagSVM, Random Forest and CART to RNA-Seq data.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/MLSeq.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL(>=2)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/MLSeq_2.18.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/MLSeq/MLSeq_2.18.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/MLSeq_2.18.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-mlseq/bioconductor-mlseq_2.18.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Machine Learning Interface for RNA-Seq Data", "tags": null, "text_prefix": false, "timestamp": 1694040904, "version": "2.18.0" }, "bioconductor-mmuphin": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "MMUPHin is an R package for meta-analysis tasks of microbiome cohorts. 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This may help in answering the question whether some genes change role between early stages (I, II) and late stages (III, IV) in breast cancer. 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Wraps C++ code from the MOODS motif calling library, which was developed by Pasi Rastas, Janne Korhonen, and Petri Martinm\u00e4ki.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/motifmatchr.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3 + file LICENSE", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/motifmatchr_1.22.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/motifmatchr/motifmatchr_1.22.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/motifmatchr_1.22.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-motifmatchr/bioconductor-motifmatchr_1.22.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Fast Motif Matching in R", "tags": null, "text_prefix": false, "timestamp": 1693457833, "version": "1.22.0" }, "bioconductor-motifstack": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The motifStack package is designed for graphic representation of multiple motifs with different similarity scores. 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MPRAnalyze can be used for quantification of enhancer activity, classification of active enhancers and comparative analyses of enhancer activity between conditions. MPRAnalyze construct a nested pair of generalized linear models (GLMs) to relate the DNA and RNA observations, easily adjustable to various experimental designs and conditions, and provides a set of rigorous statistical testig schemes.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/MPRAnalyze.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/MPRAnalyze_1.18.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/MPRAnalyze/MPRAnalyze_1.18.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/MPRAnalyze_1.18.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-mpranalyze/bioconductor-mpranalyze_1.18.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Statistical Analysis of MPRA data", "tags": null, "text_prefix": false, "timestamp": 1692372696, "version": "1.18.0" }, "bioconductor-msa": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The 'msa' package provides a unified R/Bioconductor interface to the multiple sequence alignment algorithms ClustalW, ClustalOmega, and Muscle. All three algorithms are integrated in the package, therefore, they do not depend on any external software tools and are available for all major platforms. The multiple sequence alignment algorithms are complemented by a function for pretty-printing multiple sequence alignments using the LaTeX package TeXshade.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/msa.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>= 2)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/msa_1.32.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/msa/msa_1.32.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/msa_1.32.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-msa/bioconductor-msa_1.32.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Multiple Sequence Alignment", "tags": null, "text_prefix": false, "timestamp": 1695303317, "version": "1.32.0.1" }, "bioconductor-mscoreutils": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "MsCoreUtils defines low-level functions for mass spectrometry data and is independent of any high-level data structures. These functions include mass spectra processing functions (noise estimation, smoothing, binning), quantitative aggregation functions (median polish, robust summarisation, ...), missing data imputation, data normalisation (quantiles, vsn, ...) as well as misc helper functions, that are used across high-level data structure within the R for Mass Spectrometry packages.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/MsCoreUtils.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/MsCoreUtils_1.12.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/MsCoreUtils/MsCoreUtils_1.12.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/MsCoreUtils_1.12.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-mscoreutils/bioconductor-mscoreutils_1.12.0_src_all.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "Core Utils for Mass Spectrometry Data", "tags": null, "text_prefix": false, "timestamp": 1692092135, "version": "1.12.0" }, "bioconductor-msdata": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Ion Trap positive ionization mode data in mzML file format. 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PSI mzIdentML example files for various search engines.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/data/experiment/html/msdata.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>= 2)", "post_link": true, "pre_link": false, "pre_unlink": true, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/msdata_0.40.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/msdata/msdata_0.40.0.tar.gz", "https://bioconductor.org/packages/3.17/data/experiment/src/contrib/msdata_0.40.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-msdata/bioconductor-msdata_0.40.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Various Mass Spectrometry raw data example files", "tags": null, "text_prefix": false, "timestamp": 1691562906, "version": "0.40.0" }, "bioconductor-msfeatures": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The MsFeature package defines functionality for Mass Spectrometry features. This includes functions to group (LC-MS) features based on some of their properties, such as retention time (coeluting features), or correlation of signals across samples. This packge hence allows to group features, and its results can be used as an input for the `QFeatures` package which allows to aggregate abundance levels of features within each group. This package defines concepts and functions for base and common data types, implementations for more specific data types are expected to be implemented in the respective packages (such as e.g. `xcms`). All functionality of this package is implemented in a modular way which allows combination of different grouping approaches and enables its re-use in other R packages.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/MsFeatures.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/MsFeatures_1.8.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/MsFeatures/MsFeatures_1.8.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/MsFeatures_1.8.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-msfeatures/bioconductor-msfeatures_1.8.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Functionality for Mass Spectrometry Features", 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It provides a familiar Bioconductor user experience by extending concepts from SummarizedExperiment, supporting an open-ended mix of standard data classes for individual assays, and allowing subsetting by genomic ranges or rownames. Facilities are provided for reshaping data into wide and long formats for adaptability to graphing and downstream analysis.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/MultiAssayExperiment.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Artistic-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/MultiAssayExperiment_1.26.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/MultiAssayExperiment/MultiAssayExperiment_1.26.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/MultiAssayExperiment_1.26.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-multiassayexperiment/bioconductor-multiassayexperiment_1.26.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Software for the integration of multi-omics experiments in Bioconductor", "tags": null, "text_prefix": false, "timestamp": 1692078652, "version": "1.26.0" }, "bioconductor-multiclust": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Clustering is carried out to identify patterns in transcriptomics profiles to determine clinically relevant subgroups of patients. Feature (gene) selection is a critical and an integral part of the process. Currently, there are many feature selection and clustering methods to identify the relevant genes and perform clustering of samples. However, choosing an appropriate methodology is difficult. In addition, extensive feature selection methods have not been supported by the available packages. Hence, we developed an integrative R-package called multiClust that allows researchers to experiment with the choice of combination of methods for gene selection and clustering with ease. Using multiClust, we identified the best performing clustering methodology in the context of clinical outcome. Our observations demonstrate that simple methods such as variance-based ranking perform well on the majority of data sets, provided that the appropriate number of genes is selected. However, different gene ranking and selection methods remain relevant as no methodology works for all studies.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/multiClust.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL (>= 2)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/multiClust_1.30.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/multiClust/multiClust_1.30.0.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/multiClust_1.30.0.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-multiclust/bioconductor-multiclust_1.30.0_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "multiClust: An R-package for Identifying Biologically Relevant Clusters in Cancer Transcriptome Profiles", "tags": null, "text_prefix": false, "timestamp": 1693548804, "version": "1.30.0" }, "bioconductor-multidataset": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Implementation of the BRGE's (Bioinformatic Research Group in Epidemiology from Center for Research in Environmental Epidemiology) MultiDataSet and ResultSet. 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This extension of the original HiCcompare package now allows for Hi-C experiments with more than 2 groups and multiple samples per group. multiHiCcompare operates on processed Hi-C data in the form of sparse upper triangular matrices. It accepts four column (chromosome, region1, region2, IF) tab-separated text files storing chromatin interaction matrices. multiHiCcompare provides cyclic loess and fast loess (fastlo) methods adapted to jointly normalizing Hi-C data. Additionally, it provides a general linear model (GLM) framework adapting the edgeR package to detect differences in Hi-C data in a distance dependent manner.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://bioconductor.org/packages/3.17/bioc/html/multiHiCcompare.html", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT + file LICENSE", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://bioarchive.galaxyproject.org/multiHiCcompare_1.18.1.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/Archive/multiHiCcompare/multiHiCcompare_1.18.1.tar.gz", "https://bioconductor.org/packages/3.17/bioc/src/contrib/multiHiCcompare_1.18.1.tar.gz", "https://depot.galaxyproject.org/software/bioconductor-multihiccompare/bioconductor-multihiccompare_1.18.1_src_all.tar.gz" ], "subdirs": [ "noarch" ], "summary": "Normalize and detect differences between Hi-C datasets when replicates of each experimental condition are available", "tags": null, "text_prefix": false, "timestamp": 1693633089, "version": "1.18.1" }, "bioconductor-multtest": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. Tests based on a variety of t- and F-statistics (including t-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with t-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted p-values, confidence regions and test statistic cutoffs. 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null, "home": "http://metacpan.org/pod/JSON::XS", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "unknown", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://cpan.metacpan.org/authors/id/M/ML/MLEHMANN/JSON-XS-2.34.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "JSON serialising/deserialising, done correctly and fast", "tags": null, "text_prefix": true, "timestamp": 1693175995, "version": "2.34" }, "perl-list-moreutils": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://metacpan.org/release/List-MoreUtils", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "apache_2_0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://cpan.metacpan.org/authors/id/R/RE/REHSACK/List-MoreUtils-0.430.tar.gz", "subdirs": [ "noarch" ], "summary": "Provide the stuff missing in List::Util", "tags": null, "text_prefix": true, "timestamp": 1693175850, "version": "0.430" }, "perl-list-moreutils-xs": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://metacpan.org/release/List-MoreUtils-XS", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "apache_2_0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://cpan.metacpan.org/authors/id/R/RE/REHSACK/List-MoreUtils-XS-0.430.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Provide the stuff missing in List::Util in XS", "tags": null, "text_prefix": true, "timestamp": 1693175569, "version": "0.430" }, "perl-math-cdf": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://metacpan.org/pod/Math-CDF", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Public Domain", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "http://cpan.metacpan.org/authors/id/C/CA/CALLAHAN/Math-CDF-0.1.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Generate probabilities and quantiles from several statistical probability functions", "tags": null, "text_prefix": true, "timestamp": 1699442959, "version": "0.1" }, "perl-pathtools": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://dev.perl.org/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "perl_5", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://cpan.metacpan.org/authors/id/X/XS/XSAWYERX/PathTools-3.75.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Tools for working with directory and file names", "tags": null, "text_prefix": true, "timestamp": 1693177355, "version": "3.75" }, "perl-scalar-list-utils": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://metacpan.org/pod/Scalar-List-Utils", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "perl_5", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://cpan.metacpan.org/authors/id/P/PE/PEVANS/Scalar-List-Utils-1.62.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Common Scalar and List utility subroutines", "tags": null, "text_prefix": true, "timestamp": 1693176792, "version": "1.62" }, "perl-storable": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://metacpan.org/pod/Storable", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "perl_5", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://cpan.metacpan.org/authors/id/X/XS/XSAWYERX/Storable-3.15.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "persistence for Perl data structures", "tags": null, "text_prefix": true, "timestamp": 1693177072, "version": "3.15" }, "perl-test-leaktrace": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://metacpan.org/pod/Test-LeakTrace", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "perl_5", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://cpan.metacpan.org/authors/id/L/LE/LEEJO/Test-LeakTrace-0.17.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Traces memory leaks", "tags": null, "text_prefix": true, "timestamp": 1693175707, "version": "0.17" }, "perl-version": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://metacpan.org/pod/version", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "perl_5", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://cpan.metacpan.org/authors/id/J/JP/JPEACOCK/version-0.9924.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Structured version objects", "tags": null, "text_prefix": true, "timestamp": 1693177494, "version": "0.9924" }, "pplacer": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": "https://github.com/matsen/pplacer/", "doc_source_url": null, "doc_url": null, "home": "http://matsen.fredhutch.org/pplacer/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/matsen/pplacer/releases/download/v1.1.alpha19/pplacer-linux-v1.1.alpha19.zip", "subdirs": [ "linux-aarch64" ], "summary": "Pplacer places query sequences on a fixed reference phylogenetic tree to maximize phylogenetic likelihood or posterior probability according to a reference alignment.", "tags": null, "text_prefix": false, "timestamp": 1683629320, "version": "1.1.alpha19" }, "prodigal": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://prodigal.ornl.gov/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL v3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/hyattpd/Prodigal/archive/v2.6.3.zip", "subdirs": [ "linux-aarch64" ], "summary": "Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm) is a microbial (bacterial and archaeal) gene finding program", "tags": null, "text_prefix": false, "timestamp": 1694424345, "version": "2.6.3" }, "provstore-api": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/millar/provstore-api", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/p/provstore-api/provstore-api-0.1.3.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "ProvStore API client", "tags": null, "text_prefix": false, "timestamp": 1698406570, "version": "0.1.3" }, "pybedtools": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/daler/pybedtools", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://files.pythonhosted.org/packages/58/e2/410bb188b47582e2fd2f7176173b7b7bf46e122bb17fb4422552f4a6c604/pybedtools-0.9.0.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Wraps BEDTools for use in Python and adds many additional features.", "tags": null, "text_prefix": false, "timestamp": 1688481277, "version": "0.9.0" }, "pyclone": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "PyClone is statistical model and software tool designed to infer the prevalence of point mutations in heterogeneous cancer samples. The input data for PyClone consists of a set read counts from a deep sequencing experiment, the copy number of the genomic region containing the mutation and an estimate of tumour content.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/Roth-Lab/pyclone/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "custom", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/Roth-Lab/pyclone/archive/0.13.1.tar.gz", "subdirs": [ "noarch" ], "summary": "PyClone: A probabilistic model for inferring clonal population structure from deep NGS sequencing.", "tags": null, "text_prefix": false, "timestamp": 1692559493, "version": "0.13.1" }, "pyclone-vi": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/Roth-Lab/pyclone-vi", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPLv3", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/Roth-Lab/pyclone-vi/archive/0.1.2.tar.gz", "subdirs": [ "noarch" ], "summary": "A fast method for inferring clonal population structure", "tags": null, "text_prefix": true, "timestamp": 1688435117, "version": "0.1.2" }, "pycoqc": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": "https://a-slide.github.io/pycoQC/", "home": "https://github.com/a-slide/pycoQC", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GNU General Public v3 (GPLv3)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/p/pycoQC/pycoQC-2.5.2.tar.gz", "subdirs": [ "noarch" ], "summary": "PycoQC computes metrics and generates interactive QC plots for Oxford Nanopore technologies sequencing data", "tags": null, "text_prefix": false, "timestamp": 1688448191, "version": "2.5.2" }, "pyfastx": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/lmdu/pyfastx", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": { "2.0.1": { "weak": [ "pyfastx >=2.0.1,<3.0a0" ] } }, "source_git_url": null, "source_url": "https://github.com/lmdu/pyfastx/archive/2.0.1.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "pyfastx is a python module for fast random access to sequences from plain and gzipped FASTA/Q file", "tags": null, "text_prefix": true, "timestamp": 1699669883, "version": "2.0.1" }, "pymummer": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/sanger-pathogens/pymummer", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GNU General Public License v3 (GPLv3)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/p/pymummer/pymummer-0.11.0.tar.gz", "subdirs": [ "noarch" ], "summary": "Wrapper for MUMmer", "tags": null, "text_prefix": false, "timestamp": 1695460987, "version": "0.11.0" }, "pysam": { "activate.d": false, "binary_prefix": true, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/pysam-developers/pysam", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/pysam-developers/pysam/archive/v0.21.0.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Pysam is a Python module for reading and manipulating SAM/BAM/VCF/BCF files. It's a lightweight wrapper of the htslib C-API, the same one that powers samtools, bcftools, and tabix.", "tags": null, "text_prefix": false, "timestamp": 1688435113, "version": "0.21.0" }, "pyspoa": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": "https://github.com/nanoporetech/spoa", "doc_source_url": null, "doc_url": "https://github.com/nanoporetech/spoa", "home": "https://github.com/nanoporetech/pyspoa", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": { "0.0.10": { "weak": [ "pyspoa >=0.0.10,<1.0a0" ] } }, "source_git_url": null, "source_url": null, "subdirs": [ "linux-aarch64" ], "summary": "Python binding to spoa library.", "tags": null, "text_prefix": false, "timestamp": 1699862462, "version": "0.0.10" }, "python-edlib": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/Martinsos/edlib", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT License", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/e/edlib/edlib-1.3.9.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Lightweight, super fast C/C++ (& Python) library for sequence alignment using edit (Levenshtein) distance.", "tags": null, "text_prefix": false, "timestamp": 1698907116, "version": "1.3.9" }, "python-lzo": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "Python-LZO provides Python bindings for LZO, i.e. you can access the LZO library from your Python scripts thereby compressing ordinary Python strings.", "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/jd-boyd/python-lzo", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/p/python-lzo/python-lzo-1.14.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "Python bindings for the LZO data compression library", "tags": null, "text_prefix": false, "timestamp": 1688433732, "version": "1.14" }, "pyvcf": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": "The intent of this module is to mimic the csv module in the Python stdlib, as opposed to more flexible serialization formats like JSON or YAML. vcf will attempt to parse the content of each record based on the data types specified in the meta-information lines -- specifically the \\##INFO and \\##FORMAT lines. If these lines are missing or incomplete, it will check against the reserved types mentioned in the spec. Failing that, it will just return strings.", "dev_url": "https://github.com/jamescasbon/PyVCF", "doc_source_url": null, "doc_url": "http://pyvcf.readthedocs.io", "home": "https://github.com/jamescasbon/PyVCF", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "BSD-3-Clause", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/P/PyVCF/PyVCF-0.6.8.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "A Variant Call Format (VCF) v4.0 and v4.1 parser for Python.", "tags": null, "text_prefix": true, "timestamp": 1669655627, "version": "0.6.8" }, "r-grbase": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://people.math.aau.dk/~sorenh/software/gR/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-2.0-or-later", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": { "1.9.0": { "weak": [ "r-grbase >=1.9.0,<2.0a0" ] } }, "source_git_url": null, "source_url": [ "https://cran.r-project.org/src/contrib/Archive/gRbase/gRbase_1.9.0.tar.gz", "https://cran.r-project.org/src/contrib/gRbase_1.9.0.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "The 'gRbase' package provides graphical modelling features used by e.g. the packages 'gRain', 'gRim' and 'gRc'. 'gRbase' implements graph algorithms including (i) maximum cardinality search (for marked and unmarked graphs). (ii) moralization, (iii) triangulation, (iv) creation of junction tree. 'gRbase' facilitates array operations, 'gRbase' implements functions for testing for conditional independence. 'gRbase' illustrates how hierarchical log-linear models may be implemented and describes concept of graphical meta data. The facilities of the package are documented in the book by H\u00f8jsgaard, Edwards and Lauritzen (2012, ) and in the paper by Dethlefsen and H\u00f8jsgaard, (2005, ). Please see 'citation(\"gRbase\")' for citation details. 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"https://www.x.org/releases/individual/data/xbitmaps-1.1.2.tar.bz2", "subdirs": [ "linux-aarch64" ], "summary": "Bitmaps shared between X applications", "tags": null, "text_prefix": true, "timestamp": 1699859465, "version": "1.1.2" }, "xpressplot": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/XPRESSyourself/XPRESSplot", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GPL-3.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://github.com/XPRESSyourself/XPRESSplot/archive/XPRESSplot-v0.2.5.tar.gz", "subdirs": [ "noarch" ], "summary": "A toolkit for navigating and analyzing gene expression datasets.", "tags": null, "text_prefix": false, "timestamp": 1694753319, "version": "0.2.5" }, "xtail": { "activate.d": false, 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"MIT", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.python.org/packages/source/y/yahmm/yahmm-1.1.3.zip", "subdirs": [ "linux-aarch64" ], "summary": "YAHMM is a HMM package for Python, implemented in Cython for speed.", "tags": null, "text_prefix": false, "timestamp": 1705917595, "version": "1.1.3" }, "yanagiba": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/Adamtaranto/Yanagiba", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "MIT License", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "https://pypi.io/packages/source/y/yanagiba/yanagiba-1.0.0.tar.gz", "subdirs": [ "noarch" ], "summary": "Filter short or low quality Oxford Nanopore reads which have been basecalled with Albacore.", "tags": null, "text_prefix": false, "timestamp": 1694749533, "version": "1.0.0" }, "yara": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://github.com/seqan/seqan/blob/develop/apps/yara/README.rst", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "https://raw.githubusercontent.com/seqan/seqan/develop/apps/yara/LICENSE", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": null, "subdirs": [ "linux-aarch64" ], "summary": "Yara is an exact tool for aligning DNA sequencing reads to reference genomes.", "tags": null, "text_prefix": false, "timestamp": 1694745053, "version": "1.0.2" }, "zagros": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "http://smithlabresearch.org/software/zagros/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "GNU General Public License v3 (GPLv3)", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": "http://smithlabresearch.org/downloads/zagros-1.0.0.tar.gz", "subdirs": [ "linux-aarch64" ], "summary": "zagros is a motif-discovery tool for CLIP-Seq data.", "tags": null, "text_prefix": false, "timestamp": 1694681178, "version": "1.0.0" }, "zorro": { "activate.d": false, "binary_prefix": false, "deactivate.d": false, "description": null, "dev_url": null, "doc_source_url": null, "doc_url": null, "home": "https://sourceforge.net/projects/probmask/", "icon_hash": null, "icon_url": null, "identifiers": null, "keywords": null, "license": "Apache License 2.0", "post_link": false, "pre_link": false, "pre_unlink": false, "recipe_origin": null, "run_exports": {}, "source_git_url": null, "source_url": [ "https://depot.galaxyproject.org/software/zorro/zorro_2011.12.01_src_all.tar.gz", "https://sourceforge.net/projects/probmask/files/probmask.tar.gz" ], "subdirs": [ "linux-aarch64" ], "summary": "ZORRO is a probabilistic masking program that assigns confidence scores to each column in a multiple sequence alignment.", "tags": null, "text_prefix": false, "timestamp": 1700639349, "version": "2011.12.01" } }, "subdirs": [ "linux-aarch64", "noarch" ] }