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HLA*LA—HLA typing from linearly projected graph alignments

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 lon...

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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6821427/
https://www.ncbi.nlm.nih.gov/pubmed/30942877
http://dx.doi.org/10.1093/bioinformatics/btz235
Descripción
Sumario: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.