期刊
BIOINFORMATICS
卷 35, 期 21, 页码 4394-4396出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btz235
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资金
- Intramural Research Program of the National Human Genome Research Institute, National Institutes of Health
- Jurgen Manchot Foundation
- Agence Nationale de la Recherche [ANR-11-LABX-0070_TRANSPLANTEX]
- INTERREG V European regional development fund (European Union) program (project 3.2 TRIDIAG)
- Wellcome Trust Fellowship [106289/Z/14/Z]
- European Research Council Advanced Grant [294557]
- Korean Visiting Scientist Training Award through the Korea Health Industry Development Institute - Ministry of Health& Welfare, Republic of Korea [HI17C2098]
- Korea Health Promotion Institute [HI17C2098000019] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
- European Research Council (ERC) [294557] Funding Source: European Research Council (ERC)
- NATIONAL HUMAN GENOME RESEARCH INSTITUTE [ZIAHG200398] Funding Source: NIH RePORTER
A Summary: HLA*LA implements a new graph alignment model for human leukocyte antigen (HLA) type inference, based on the projection of linear alignments onto a variation graph. It enables accurate HLA type inference from whole-genome (99% accuracy) and whole-exome (93% accuracy) Illumina data; from long-read Oxford Nanopore and Pacific Biosciences data (98% accuracy for whole-genome and targeted data) and from genome assemblies. Computational requirements for a typical sample vary between 0.7 and 14 CPU hours per sample.
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