HLALA—HLA typing from linearly projected graph alignments

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;...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Bioinformatics Jg. 35; H. 21; S. 4394 - 4396
Hauptverfasser: 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
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England Oxford University Press 01.11.2019
Oxford University Press (OUP)
Schlagworte:
Applications Notes
Genome
High-Throughput Nucleotide Sequencing
Histocompatibility Testing
Humans
Immunology
Life Sciences
Sequence Analysis, DNA
Software
ISSN:1367-4803, 1367-4811, 1460-2059, 1367-4811
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
PMCID: PMC6821427
ISSN:1367-4803
1367-4811
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btz235