Analyzes mutation patterns in Rep-Seq data to identify novel V segment alleles, and also constructs a personalized germline database containing the specific set of alleles carried by a subject. This information is then used to improve the initial V segment assignments from existing tools, like IMGT/HighV-QUEST. The application of TIgGER to Rep-Seq data from seven subjects identified 11 novel V segment alleles, including at least one in every subject examined. These novel alleles constituted 13% of the total number of unique alleles in these subjects, and impacted 3% of V(D)J segment assignments. These results reinforce the highly polymorphic nature of human Ig V genes, and suggest that many novel alleles remain to be discovered. The integration of TIgGER into Rep-Seq processing pipelines will increase the accuracy of V segment assignments, thus improving B-cell repertoire analyses.

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TIgGER versioning

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TIgGER classification

  • Animals
  • Fungi
  • Plants
  • Protists

TIgGER specifications

Software type:
Package
Restrictions to use:
Academic users only
Output data:
A list of V/D/J alleles detected in sample
Operating system:
Unix/Linux, Mac OS, Windows
License:
CC Attribution
Version:
TIgGER version 2.0
Interface:
Command line interface
Input data:
RepSeq sequencing reads
Biological technology:
Illumina, Roche
Programming languages:
R
Computer skills:
Advanced
Stability:
Stable

TIgGER support

Maintainer

Credits

Publications

  • (Gadala-Maria et al., 2015) Automated analysis of high-throughput B-cell sequencing data reveals a high frequency of novel immunoglobulin V gene segment alleles. PNAS.
    PMID: 25675496

Institution(s)

Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511

Link to literature

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