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Kourami: graph-guided assembly for novel human leukocyte antigen allele discovery
1Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
Abstract:
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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