r-cran-tigger
Infers new Immunoglobulin alleles from Rep-Seq Data
Description
Summary: 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
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Homepage
https://cran.r-project.org/package=tigger
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