期刊
GENOME BIOLOGY
卷 19, 期 -, 页码 -出版社
BMC
DOI: 10.1186/s13059-018-1388-2
关键词
-
资金
- 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
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据