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HLA*LA – HLA typing from linearly projected graph alignments

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).

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

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