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.
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