Journal
GENOME BIOLOGY
Volume 19, Issue -, Pages -Publisher
BMC
DOI: 10.1186/s13059-018-1388-2
Keywords
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Funding
- Gordon and Betty Moore Foundation's Data-Driven Discovery Initiative [GBMF4554]
- U.S. National Science Foundation [CCF-1256087, CCF-1319998]
- U.S. National Institutes of Health [R01HG007104]
- Shurl and Kay Curci Foundation
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Accurate typing of human leukocyte antigen (HLA) is important because HLA genes play important roles in immune responses and disease genesis. Previously available computational methods are database-matching approaches and their outputs are inherently limited by the completeness of already known types, making them unsuitable for discovery of novel alleles. We have developed a graph-guided assembly technique for classical HLA genes, which can construct allele sequences given high-coverage whole-genome sequencing data. Our method delivers highly accurate HLA typing, comparable to the current state-of-the-art methods. Using various data, we also demonstrate that our method can type novel alleles.
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