BUSCO Applications from Quality Assessments to Gene Prediction and Phylogenomics

Genomics promises comprehensive surveying of genomes and metagenomes, but rapidly changing technologies and expanding data volumes make evaluation of completeness a challenging task. Technical sequencing quality metrics can be complemented by quantifying completeness of genomic data sets in terms of...

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Published in	Molecular biology and evolution Vol. 35; no. 3; pp. 543 - 548
Main Authors	Waterhouse, Robert M, Seppey, Mathieu, Simão, Felipe A, Manni, Mosè, Ioannidis, Panagiotis, Klioutchnikov, Guennadi, Kriventseva, Evgenia V, Zdobnov, Evgeny M
Format	Journal Article
Language	English
Published	United States Oxford University Press 01.03.2018
Subjects	Arthropods Completeness Datasets Fast Track Genomics Metagenomics Prokaryotes Quality assessment Quality control Vertebrates transcriptomics evolution metagenomics bioinformatics
Online Access	Get full text
ISSN	0737-4038 1537-1719 1537-1719
DOI	10.1093/molbev/msx319

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Abstract	Genomics promises comprehensive surveying of genomes and metagenomes, but rapidly changing technologies and expanding data volumes make evaluation of completeness a challenging task. Technical sequencing quality metrics can be complemented by quantifying completeness of genomic data sets in terms of the expected gene content of Benchmarking Universal Single-Copy Orthologs (BUSCO, http://busco.ezlab.org). The latest software release implements a complete refactoring of the code to make it more flexible and extendable to facilitate high-throughput assessments. The original six lineage assessment data sets have been updated with improved species sampling, 34 new subsets have been built for vertebrates, arthropods, fungi, and prokaryotes that greatly enhance resolution, and data sets are now also available for nematodes, protists, and plants. Here, we present BUSCO v3 with example analyses that highlight the wide-ranging utility of BUSCO assessments, which extend beyond quality control of genomics data sets to applications in comparative genomics analyses, gene predictor training, metagenomics, and phylogenomics.
AbstractList	Genomics promises comprehensive surveying of genomes and metagenomes, but rapidly changing technologies and expanding data volumes make evaluation of completeness a challenging task. Technical sequencing quality metrics can be complemented by quantifying completeness of genomic data sets in terms of the expected gene content of Benchmarking Universal Single-Copy Orthologs (BUSCO, http://busco.ezlab.org ). The latest software release implements a complete refactoring of the code to make it more flexible and extendable to facilitate high-throughput assessments. The original six lineage assessment data sets have been updated with improved species sampling, 34 new subsets have been built for vertebrates, arthropods, fungi, and prokaryotes that greatly enhance resolution, and data sets are now also available for nematodes, protists, and plants. Here, we present BUSCO v3 with example analyses that highlight the wide-ranging utility of BUSCO assessments, which extend beyond quality control of genomics data sets to applications in comparative genomics analyses, gene predictor training, metagenomics, and phylogenomics. Genomics promises comprehensive surveying of genomes and metagenomes, but rapidly changing technologies and expanding data volumes make evaluation of completeness a challenging task. Technical sequencing quality metrics can be complemented by quantifying completeness of genomic data sets in terms of the expected gene content of Benchmarking Universal Single-Copy Orthologs (BUSCO, http://busco.ezlab.org). The latest software release implements a complete refactoring of the code to make it more flexible and extendable to facilitate high-throughput assessments. The original six lineage assessment data sets have been updated with improved species sampling, 34 new subsets have been built for vertebrates, arthropods, fungi, and prokaryotes that greatly enhance resolution, and data sets are now also available for nematodes, protists, and plants. Here, we present BUSCO v3 with example analyses that highlight the wide-ranging utility of BUSCO assessments, which extend beyond quality control of genomics data sets to applications in comparative genomics analyses, gene predictor training, metagenomics, and phylogenomics. Genomics promises comprehensive surveying of genomes and metagenomes, but rapidly changing technologies and expanding data volumes make evaluation of completeness a challenging task. Technical sequencing quality metrics can be complemented by quantifying completeness of genomic data sets in terms of the expected gene content of Benchmarking Universal Single-Copy Orthologs (BUSCO, http://busco.ezlab.org). The latest software release implements a complete refactoring of the code to make it more flexible and extendable to facilitate high-throughput assessments. The original six lineage assessment data sets have been updated with improved species sampling, 34 new subsets have been built for vertebrates, arthropods, fungi, and prokaryotes that greatly enhance resolution, and data sets are now also available for nematodes, protists, and plants. Here, we present BUSCO v3 with example analyses that highlight the wide-ranging utility of BUSCO assessments, which extend beyond quality control of genomics data sets to applications in comparative genomics analyses, gene predictor training, metagenomics, and phylogenomics.Genomics promises comprehensive surveying of genomes and metagenomes, but rapidly changing technologies and expanding data volumes make evaluation of completeness a challenging task. Technical sequencing quality metrics can be complemented by quantifying completeness of genomic data sets in terms of the expected gene content of Benchmarking Universal Single-Copy Orthologs (BUSCO, http://busco.ezlab.org). The latest software release implements a complete refactoring of the code to make it more flexible and extendable to facilitate high-throughput assessments. The original six lineage assessment data sets have been updated with improved species sampling, 34 new subsets have been built for vertebrates, arthropods, fungi, and prokaryotes that greatly enhance resolution, and data sets are now also available for nematodes, protists, and plants. Here, we present BUSCO v3 with example analyses that highlight the wide-ranging utility of BUSCO assessments, which extend beyond quality control of genomics data sets to applications in comparative genomics analyses, gene predictor training, metagenomics, and phylogenomics.
Author	Manni, Mosè Seppey, Mathieu Ioannidis, Panagiotis Kriventseva, Evgenia V Waterhouse, Robert M Simão, Felipe A Zdobnov, Evgeny M Klioutchnikov, Guennadi
AuthorAffiliation	Department of Genetic Medicine and Development, University of Geneva Medical School and Swiss Institute of Bioinformatics, Geneva, Switzerland
AuthorAffiliation_xml	– name: Department of Genetic Medicine and Development, University of Geneva Medical School and Swiss Institute of Bioinformatics, Geneva, Switzerland
Author_xml	– sequence: 1 givenname: Robert M surname: Waterhouse fullname: Waterhouse, Robert M organization: Department of Genetic Medicine and Development, University of Geneva Medical School and Swiss Institute of Bioinformatics, Geneva, Switzerland – sequence: 2 givenname: Mathieu surname: Seppey fullname: Seppey, Mathieu organization: Department of Genetic Medicine and Development, University of Geneva Medical School and Swiss Institute of Bioinformatics, Geneva, Switzerland – sequence: 3 givenname: Felipe A surname: Simão fullname: Simão, Felipe A organization: Department of Genetic Medicine and Development, University of Geneva Medical School and Swiss Institute of Bioinformatics, Geneva, Switzerland – sequence: 4 givenname: Mosè surname: Manni fullname: Manni, Mosè organization: Department of Genetic Medicine and Development, University of Geneva Medical School and Swiss Institute of Bioinformatics, Geneva, Switzerland – sequence: 5 givenname: Panagiotis surname: Ioannidis fullname: Ioannidis, Panagiotis organization: Department of Genetic Medicine and Development, University of Geneva Medical School and Swiss Institute of Bioinformatics, Geneva, Switzerland – sequence: 6 givenname: Guennadi surname: Klioutchnikov fullname: Klioutchnikov, Guennadi organization: Department of Genetic Medicine and Development, University of Geneva Medical School and Swiss Institute of Bioinformatics, Geneva, Switzerland – sequence: 7 givenname: Evgenia V surname: Kriventseva fullname: Kriventseva, Evgenia V organization: Department of Genetic Medicine and Development, University of Geneva Medical School and Swiss Institute of Bioinformatics, Geneva, Switzerland – sequence: 8 givenname: Evgeny M surname: Zdobnov fullname: Zdobnov, Evgeny M organization: Department of Genetic Medicine and Development, University of Geneva Medical School and Swiss Institute of Bioinformatics, Geneva, Switzerland
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/29220515$$D View this record in MEDLINE/PubMed
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ContentType	Journal Article
Copyright	The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. 2017
Copyright_xml	– notice: The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. – notice: The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. 2017
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Keywords	transcriptomics evolution metagenomics bioinformatics
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License	The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
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Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 These authors are joint Second Authors. Present address: Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland Associate editor: Michael Rosenberg
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