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SUMMARY: HLA*LA implements a new graph alignment model for 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 online.

Original publication

DOI

10.1093/bioinformatics/btz235

Type

Journal article

Journal

Bioinformatics

Publication Date

03/04/2019