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April 2, 2019Bioinformatics169 citationsOpen Access

HLA*LA—HLA typing from linearly projected graph alignments

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ADAlexander DiltheyAMAlexander J. MentzerRCRaphaël Carapito

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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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Dilthey et al. (2019) studied this question.

synapsesocial.com/papers/69ff7d6ab124fe58198576bbhttps://doi.org/10.1093/bioinformatics/btz235
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