Infers the V genotype of an individual from immunoglobulin (Ig)
repertoire sequencing data (AIRR-Seq, Rep-Seq). Includes detection of
any novel alleles. This information is then used to correct existing V
allele calls from among the sample sequences.
Citations:
Gadala-Maria, et al (2015)
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.)
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.
reassignAlleles with non-existent v_call column.generateEvidence that was reporting amino acids mutations as
NA instead of gaps.Bug Fixes:
reassignAlleles occuring with single match genotypes.selectNovel improperly removing all identical novel alleles, rather
than keeping a single entry.genotypeFasta will now retain IMGT-numbering spacers as . characters
instead of converting them to - characters.findNovelAlleles causing overly aggressive minimum sequence
threshold filtering.getPopularMutationCount.New Features:
inferGenotypeBayesian function.generateEvidence to build a complete evidence table
from the results of findNovelAlleles, inferGenotype,
inferGenotypeBayesian, and reassignAlleles.findNovelAlleles
and adjusted the definitions/names of some existing columns.keep_gene argument of reassignAlleles to provide
options for maintaining reassignments at the gene (previous TRUE behavior),
family, or repertoire level.findNovelAlleles.Backwards Incompatible Refactors:
germline_ighv, sample_db, genotype and
novel_df to GermlineIGHV, SampleDb, SampleGenotype and SampleNovel,
respectively.novel_df argument to novel in selectNovel, inferGenotype,
and genotypeFasta.novel_df_row argument to novel_row in plotNovel.inferGenotype was alter for clarity.reassignAlleles so that it returns the
input data.frame with the V_CALL_GENOTYPED column appended or overwritten.cleanSeqs will no longer replace . characters with -.findNovelAlleles.inferGenotype would break when performing check for alleles
that could not be distinguished.inferGenotype would break if all sequences submitted were
from a single gene and find_unmutated was set to TRUE.findNovelAlleles() was not running in parallel, even
when nproc > 1.nproc=1 in findNovelAlleles().