Infers Novel Immunoglobulin Alleles from Sequencing Data.
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.