Paquet : r-cran-tigger (1.0.0-1)

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Infers new Immunoglobulin alleles from Rep-Seq Data

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 Change-O.

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