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. 2019 Nov 1;35(21):4394-4396.
doi: 10.1093/bioinformatics/btz235.

HLA*LA-HLA typing from linearly projected graph alignments

Alexander T Dilthey  1   2   3 , Alexander J Mentzer  3   4 , Raphael Carapito  5   6 , Clare Cutland  7   8 , Nezih Cereb  9 , Shabir A Madhi  7   8 , Arang Rhie  2 , Sergey Koren  2 , Seiamak Bahram  5   6 , Gil McVean  3   4 , Adam M Phillippy  2
Affiliations

HLA*LA-HLA typing from linearly projected graph alignments

Alexander T Dilthey et al. Bioinformatics. .

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.

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References

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