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Hostile: accurate decontamination of microbial host sequences.
Constantinides, Bede; Hunt, Martin; Crook, Derrick W.
Afiliação
  • Constantinides B; NDM Experimental Medicine, University of Oxford, John Radcliffe Hospital, Oxfordshire OX3 9DU, United Kingdom.
  • Hunt M; The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, John Radcliffe Hospital, Oxfordshire OX3 9DU, United Kingdom.
  • Crook DW; NDM Experimental Medicine, University of Oxford, John Radcliffe Hospital, Oxfordshire OX3 9DU, United Kingdom.
Bioinformatics ; 39(12)2023 12 01.
Article em En | MEDLINE | ID: mdl-38039142
ABSTRACT
MOTIVATION Microbial sequences generated from clinical samples are often contaminated with human host sequences that must be removed for ethical and legal reasons. Care must be taken to excise host sequences without inadvertently removing target microbial sequences to the detriment of downstream analyses such as variant calling and de novo assembly.

RESULTS:

To facilitate accurate host decontamination of both short and long sequencing reads, we developed Hostile, a tool capable of accurate host read removal using a laptop. We demonstrate that our approach removes at least 99.6% of real human reads and retains at least 99.989% of simulated bacterial reads. Using Hostile with a masked reference genome further increases bacterial read retention (≥99.997%) with negligible (≤0.001%) reduction in human read removal performance. Compared with an existing tool, Hostile removes 21%-23% more human short reads and 21-43 times fewer bacterial reads, typically in less time. AVAILABILITY AND IMPLEMENTATION Hostile is implemented as an MIT-licensed Python package available from https//github.com/bede/hostile together with supplementary material.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Descontaminação Limite: Humans Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Descontaminação Limite: Humans Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido