HLA*LA – HLA typing from linearly projected graph alignments.

Authors: Dilthey, Alexander T and Mentzer, Alexander J and Carapito, Raphael and Cutland, Clare and Cereb, Nezih and Madhi, Shabir A and Rhie, Arang and Koren, Sergey and Bahram, Seiamak and McVean, Gil and Phillippy, Adam M

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.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 data are available online. © The Author(s) 2019. Published by Oxford University Press.

Journal: Bioinformatics
DOI: 10.1093/bioinformatics/btz235
Year: 2019

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