May 18, 2019 Software Open Access

Marcelino, V. R.; Clausen, P.T.C.L; Buchmann, J.P.; Wille, M.; Iredell, J.R.; Meyer, W.; Lund, O.; Sorrell, T.C.; Holmes, E.C.

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  <identifier identifierType="DOI">10.5281/zenodo.3668497</identifier>
  <creators>
    <creator>
      <creatorName>Marcelino, V. R.</creatorName>
      <givenName>V. R.</givenName>
      <familyName>Marcelino</familyName>
      <affiliation>The University of Sydney</affiliation>
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    <creator>
      <creatorName>Clausen, P.T.C.L</creatorName>
      <givenName>P.T.C.L</givenName>
      <familyName>Clausen</familyName>
      <affiliation>Technical University of Denmark</affiliation>
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    <creator>
      <creatorName>Buchmann, J.P.</creatorName>
      <givenName>J.P.</givenName>
      <familyName>Buchmann</familyName>
      <affiliation>The University of Sydney</affiliation>
    </creator>
    <creator>
      <creatorName>Wille, M.</creatorName>
      <givenName>M.</givenName>
      <familyName>Wille</familyName>
      <affiliation>The Peter Doherty Institute for Infection and Immunity</affiliation>
    </creator>
    <creator>
      <creatorName>Iredell, J.R.</creatorName>
      <givenName>J.R.</givenName>
      <familyName>Iredell</familyName>
      <affiliation>The University of Sydney</affiliation>
    </creator>
    <creator>
      <creatorName>Meyer, W.</creatorName>
      <givenName>W.</givenName>
      <familyName>Meyer</familyName>
      <affiliation>The University of Sydney</affiliation>
    </creator>
    <creator>
      <creatorName>Lund, O.</creatorName>
      <givenName>O.</givenName>
      <familyName>Lund</familyName>
      <affiliation>Technical University of Denmark</affiliation>
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    <creator>
      <creatorName>Sorrell, T.C.</creatorName>
      <givenName>T.C.</givenName>
      <familyName>Sorrell</familyName>
      <affiliation>The University of Sydney</affiliation>
    </creator>
    <creator>
      <creatorName>Holmes, E.C.</creatorName>
      <givenName>E.C.</givenName>
      <familyName>Holmes</familyName>
      <affiliation>The University of Sydney</affiliation>
    </creator>
  </creators>
  <titles>
    <title>CCMetagen: comprehensive and accurate identification of eukaryotes and prokaryotes in metagenomic data</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>metagenomics</subject>
    <subject>microbiome</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2019-05-18</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Software"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3668497</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsDocumentedBy" resourceTypeGeneral="Preprint">10.1101/641332</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3668496</relatedIdentifier>
  </relatedIdentifiers>
  <version>1.0.0</version>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;CCMetagen is a software to identify taxa from metagenome data. This repository contains CCMetagen version 1.0.0, which was benchmarked with other software in the original CCMetagen publication.&lt;/p&gt;

&lt;p&gt;High-throughput sequencing of DNA and RNA from environmental and host-associated samples (metagenomics and metatranscriptomics) is a powerful tool to assess which organisms are present in a sample. Taxonomic identification software usually align individual short sequence reads to a reference database, sometimes containing taxa with complete genomes only. This is a challenging task given that different species can share identical sequence regions and complete genome sequences are only available for a fraction of organisms. A recently developed approach to map sequence reads to reference databases involves weighing all high scoring read-mappings to the data base as a whole to produce better-informed alignments. We used this novel concept in read mapping to develop a highly accurate metagenomic classification pipeline named CCMetagen. Our pipeline substantially outperforms other commonly used software in identifying bacteria and fungi, and can efficiently use the entire NCBI nucleotide collection as a reference to detect species with incomplete genome data from all biological kingdoms. CCMetagen is user-friendly and the results can be easily integrated into microbial community analysis software for streamlined and automated microbiome studies.&lt;/p&gt;</description>
  </descriptions>
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