PhylOligo: a package to identify contaminant or untargeted organism sequences in genome assemblies

MOTIVATION: Genome sequencing projects sometimes uncover more organisms than expected, especially for complex and/or non-model organisms. It is therefore useful to develop software to identify mix of organisms from genome sequence assemblies. RESULTS: Here we present PhylOligo, a new package includi...

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Autores principales: Mallet, Ludovic, Bitard-Feildel, Tristan, Cerutti, Franck, Chiapello, Hélène
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860033/
https://www.ncbi.nlm.nih.gov/pubmed/28637232
http://dx.doi.org/10.1093/bioinformatics/btx396
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author Mallet, Ludovic
Bitard-Feildel, Tristan
Cerutti, Franck
Chiapello, Hélène
author_facet Mallet, Ludovic
Bitard-Feildel, Tristan
Cerutti, Franck
Chiapello, Hélène
author_sort Mallet, Ludovic
collection PubMed
description MOTIVATION: Genome sequencing projects sometimes uncover more organisms than expected, especially for complex and/or non-model organisms. It is therefore useful to develop software to identify mix of organisms from genome sequence assemblies. RESULTS: Here we present PhylOligo, a new package including tools to explore, identify and extract organism-specific sequences in a genome assembly using the analysis of their DNA compositional characteristics. AVAILABILITY AND IMPLEMENTATION: The tools are written in Python3 and R under the GPLv3 Licence and can be found at https://github.com/itsmeludo/Phyloligo/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-58600332018-03-23 PhylOligo: a package to identify contaminant or untargeted organism sequences in genome assemblies Mallet, Ludovic Bitard-Feildel, Tristan Cerutti, Franck Chiapello, Hélène Bioinformatics Applications Notes MOTIVATION: Genome sequencing projects sometimes uncover more organisms than expected, especially for complex and/or non-model organisms. It is therefore useful to develop software to identify mix of organisms from genome sequence assemblies. RESULTS: Here we present PhylOligo, a new package including tools to explore, identify and extract organism-specific sequences in a genome assembly using the analysis of their DNA compositional characteristics. AVAILABILITY AND IMPLEMENTATION: The tools are written in Python3 and R under the GPLv3 Licence and can be found at https://github.com/itsmeludo/Phyloligo/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2017-10-15 2017-06-15 /pmc/articles/PMC5860033/ /pubmed/28637232 http://dx.doi.org/10.1093/bioinformatics/btx396 Text en © The Author 2017. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Applications Notes
Mallet, Ludovic
Bitard-Feildel, Tristan
Cerutti, Franck
Chiapello, Hélène
PhylOligo: a package to identify contaminant or untargeted organism sequences in genome assemblies
title PhylOligo: a package to identify contaminant or untargeted organism sequences in genome assemblies
title_full PhylOligo: a package to identify contaminant or untargeted organism sequences in genome assemblies
title_fullStr PhylOligo: a package to identify contaminant or untargeted organism sequences in genome assemblies
title_full_unstemmed PhylOligo: a package to identify contaminant or untargeted organism sequences in genome assemblies
title_short PhylOligo: a package to identify contaminant or untargeted organism sequences in genome assemblies
title_sort phyloligo: a package to identify contaminant or untargeted organism sequences in genome assemblies
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860033/
https://www.ncbi.nlm.nih.gov/pubmed/28637232
http://dx.doi.org/10.1093/bioinformatics/btx396
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AT ceruttifranck phyloligoapackagetoidentifycontaminantoruntargetedorganismsequencesingenomeassemblies
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