Allelic decomposition and exact genotyping of highly polymorphic and structurally variant genes

Ibrahim Numanagić, Salem Malikić, Michael Ford, Xiang Qin, Lorraine Toji, Milan Radovich, Todd C. Skaar, Victoria M. Pratt, Bonnie Berger, Steve Scherer and S. Cenk Sahinalp ()
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Ibrahim Numanagić: Simon Fraser University
Salem Malikić: Simon Fraser University
Michael Ford: Simon Fraser University
Xiang Qin: Baylor College of Medicine Human Genome Sequencing Center
Lorraine Toji: Coriell Institute for Medical Research
Milan Radovich: Indiana University School of Medicine
Todd C. Skaar: Indiana University School of Medicine
Victoria M. Pratt: Indiana University School of Medicine
Bonnie Berger: Massachusetts Institute of Technology
Steve Scherer: Baylor College of Medicine Human Genome Sequencing Center
S. Cenk Sahinalp: Indiana University

Nature Communications, 2018, vol. 9, issue 1, 1-11

Abstract: Abstract High-throughput sequencing provides the means to determine the allelic decomposition for any gene of interest—the number of copies and the exact sequence content of each copy of a gene. Although many clinically and functionally important genes are highly polymorphic and have undergone structural alterations, no high-throughput sequencing data analysis tool has yet been designed to effectively solve the full allelic decomposition problem. Here we introduce a combinatorial optimization framework that successfully resolves this challenging problem, including for genes with structural alterations. We provide an associated computational tool Aldy that performs allelic decomposition of highly polymorphic, multi-copy genes through using whole or targeted genome sequencing data. For a large diverse sequencing data set, Aldy identifies multiple rare and novel alleles for several important pharmacogenes, significantly improving upon the accuracy and utility of current genotyping assays. As more data sets become available, we expect Aldy to become an essential component of genotyping toolkits.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-03273-1

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DOI: 10.1038/s41467-018-03273-1

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