R Tools for Inferring New Immunoglobulin Alleles from Rep-Seq Data

Infers the V genotype of an individual from immunoglobulin (Ig) repertoire-sequencing (Rep-Seq) data, including detection of any novel alleles. This information is then used to correct existing V allele calls from among the sample sequences.

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.


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


Version 0.2.11 September 21, 2017

  • Improved memory utilization in findNovelAlleles.

Version 0.2.10 July 1, 2017

  • Bugfix wherein inferGenotype would break when performing check for alleles that could not be distinguished.

Version May 16, 2017

  • Bugfix wherein inferGenotype would break if all sequences submitted were from a single gene and find_unmutated was set to TRUE.

Version 0.2.9: March 24, 2017

  • License changed to Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0).

Version 0.2.8: August 26, 2016

  • Bugfix following recent update of alakazam (0.2.5) to import selectively.
  • Removed unneeded dependency on shazam package (not needed as of

Version 0.2.7: July 24, 2016

  • More updates to work with the latest version of dplyr (0.5.0).
  • Bugfix in findNovelAlleles when allele passed germline_min but not min_seqs.
  • Fixed vignette typo and updated findUnmutatedCalls man page.

Version 0.2.6: July 01, 2016

  • Updated code to work with the latest version of dplyr (0.5.0).

Version June 10, 2016

  • Fixed a bug werein findNovelAlleles() was not running in parallel, even when nproc > 1.
  • Changed default to nproc=1 in findNovelAlleles().

Version 0.2.5: June 07, 2016

  • Initial CRAN release.

Reference manual

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0.2.11 by Jason Vander Heiden, 9 months ago


Report a bug at https://bitbucket.org/kleinstein/tigger/issues

Browse source code at https://github.com/cran/tigger

Authors: Daniel Gadala-Maria [aut], Jason Vander Heiden [ctb, cre], Steven Kleinstein [aut, cph]

Documentation:   PDF Manual  

CC BY-SA 4.0 license

Imports alakazam, tidyr, dplyr, doParallel, foreach, graphics, grid, iterators, lazyeval, parallel, stats

Depends on ggplot2

Suggests knitr, testthat

See at CRAN