Package: MSiP
Type: Package
Title: 'MassSpectrometry' Interaction Prediction
Version: 1.3.7
Authors@R: c(
    person("Matineh", "Rahmatbakhsh", , "matinerb.94@gmail.com", c("aut", "cre")))
Description: The 'MSiP' is a computational approach to predict protein-protein interactions from large-scale affinity purification mass 'spectrometry' (AP-MS) data. This approach includes both spoke and matrix models for interpreting AP-MS data in a network context. The "spoke" model considers only bait-prey interactions, whereas the "matrix" model assumes that each of the identified proteins (baits and prey) in a given AP-MS experiment interacts with each of the others. The spoke model has a high false-negative rate, whereas the matrix model has a high false-positive rate. Although, both statistical models have merits, a combination of both models has shown to increase the performance of machine learning classifiers in terms of their capabilities in discrimination between true and false positive interactions.
Depends: R (>= 3.6.0)
Imports: dplyr (>= 1.0.6), tibble (>= 3.1.2), tidyr (>= 1.1.3),
        magrittr (>= 2.0.1), plyr (>= 1.8.6), PRROC (>= 1.3.1), caret
        (>= 6.0.88), e1071 (>= 1.7.7), mice (>= 3.13.0), pROC (>=
        1.17.0.1), ranger (>= 0.12.1)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: knitr, markdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-06-16 18:52:36 UTC; Matine
Author: Matineh Rahmatbakhsh [aut, cre]
Maintainer: Matineh Rahmatbakhsh <matinerb.94@gmail.com>
Repository: CRAN
Date/Publication: 2021-06-17 08:20:05 UTC
Built: R 4.0.5; ; 2022-04-21 13:27:22 UTC; windows
