HLALA—HLA typing from linearly projected graph alignments - Dilthey, Alexander T; Mentzer, Alexander J; Carapito, Raphael; Cutland, Clare; Cereb, Nezih; Madhi, Shabir A; Rhie, Arang; Koren, Sergey; Bahram, Seiamak; McVean, Gil; Phillippy, Adam M (Bioinformatics, 2019)
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.