Journal
BIOINFORMATICS
Volume 35, Issue 22, Pages 4840-4842Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btz481
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Funding
- European Union's Horizon 2020 research and innovation program [825821]
- ISF [832/16]
- H2020 Societal Challenges Programme [825821] Funding Source: H2020 Societal Challenges Programme
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A Summary: Antibody haplotype inference (chromosomal phasing) may have clinical implications for the identification of genetic predispositions to diseases. Yet, our knowledge of the genomic loci encoding for the variable regions of the antibody is only partial, mostly due to the challenge of aligning short reads from genome sequencing to these highly repetitive loci. A powerful approach to infer the content of these loci relies on analyzing repertoires of rearranged V(D)J sequences. We present here RAbHIT, an R Haplotype Antibody Inference Tool, that implements a novel algorithm to infer V(D)J haplotypes by adapting a Bayesian framework. RAbHIT offers inference of haplotype and gene deletions. It may be applied to sequences from naive and non-naive B-cells, sequenced by different library preparation protocols.
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