Fast and accurate HLA typing from short-read next-generation sequence data with xHLA

著者: Chao Xie, Zhen Xuan Yeo, Marie Wong, Jason Piper, Tao Long, Ewen F. Kirkness, William Biggs, Ken Bloom, Stephen R. Spellman, Cynthia Vierra‐Green, Colleen A. Brady, Richard H. Scheuermann, Amalio Telenti, Sally Howard, Suzanne Brewerton, Yaron Turpaz, J. Craig Venter - Proceedings of the National Academy of Sciences, PNAS 2017 被引用: 158

Significance Regulation of the human immune system is largely controlled by the HLA gene complex on chromosome 6 and is important in infectious disease immunity, graft rejection, autoimmunity, and cancer. HLA typing is traditionally performed by serotyping and/or targeted sequencing. However, the advent of precision medicine and cheaper personal genome sequencing has sprung an unmet need for a fast and accurate way of predicting HLA types from short-read sequencing data. Here, we present xHLA, an algorithm for HLA typing based on translated short reads, exhaustive multiple sequence alignment-based alignment expansion, and iterative solution set refinement that is also faster and more accurate than existing methods. Results are achievable within minutes and could greatly benefit individuals who have had their genome sequenced.