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ABSTRACT: 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.Availability and implementation
HLA*LA is implemented in C++ and Perl and freely available as a bioconda package or from https://github.com/DiltheyLab/HLA-LA (GPL v3).Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Dilthey AT
PROVIDER: S-EPMC6821427 | biostudies-literature | 2019 Nov
REPOSITORIES: biostudies-literature
Dilthey Alexander T AT Mentzer Alexander J AJ Carapito Raphael R Cutland Clare C Cereb Nezih N Madhi Shabir A SA Rhie Arang A Koren Sergey S Bahram Seiamak S McVean Gil G Phillippy Adam M AM
Bioinformatics (Oxford, England) 20191101 21
<h4>Summary</h4>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. ...[more]