TIgGER

High-throughput sequencing of B cell immunoglobulin receptors is providing unprecedented insight into adaptive immunity. A key step in analyzing these data involves assignment of the germline V, D and J gene segment alleles that comprise each immunoglobulin sequence by matching them against a database of known V(D)J alleles. However, this process will fail for sequences that utilize previously undetected alleles, whose frequency in the population is unclear.

TIgGER is a computational method that significantly improves V(D)J allele assignments by first determining the complete set of gene segments carried by an individual (including novel alleles) from V(D)J-rearrange sequences. TIgGER can then infer a subject’s genotype from these sequences, and use this genotype to correct the initial V(D)J allele assignments.

The application of TIgGER continues to identify a surprisingly high frequency of novel alleles in humans, highlighting the critical need for this approach. (TIgGER, however, can and has been used with data from other species.)

Core Abilities

• Detecting novel alleles
• Inferring a subject’s genotype
• Correcting preliminary allele calls

Required Input

• A table of sequences from a single individual, with columns containing the following:
  • V(D)J-rearranged nucleotide sequence (in IMGT-gapped format)
  • Preliminary V allele calls
  • Preliminary J allele calls
  • Length of the junction region
• Germline Ig sequences in IMGT-gapped fasta format (e.g., as those downloaded from IMGT/GENE-DB

The former can be created through the use of IMGT/HighV-QUEST and Change-O.

Contact

For help, questions, or suggestions, please contact the Immcantation Group or use the issue tracker.