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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{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>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.</p>\n\n<p>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.</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "The University of Sydney", 
      "@type": "Person", 
      "name": "Marcelino, V. R."
    }, 
    {
      "affiliation": "Technical University of Denmark", 
      "@type": "Person", 
      "name": "Clausen, P.T.C.L"
    }, 
    {
      "affiliation": "The University of Sydney", 
      "@type": "Person", 
      "name": "Buchmann, J.P."
    }, 
    {
      "affiliation": "The Peter Doherty Institute for Infection and Immunity", 
      "@type": "Person", 
      "name": "Wille, M."
    }, 
    {
      "affiliation": "The University of Sydney", 
      "@type": "Person", 
      "name": "Iredell, J.R."
    }, 
    {
      "affiliation": "The University of Sydney", 
      "@type": "Person", 
      "name": "Meyer, W."
    }, 
    {
      "affiliation": "Technical University of Denmark", 
      "@type": "Person", 
      "name": "Lund, O."
    }, 
    {
      "affiliation": "The University of Sydney", 
      "@type": "Person", 
      "name": "Sorrell, T.C."
    }, 
    {
      "affiliation": "The University of Sydney", 
      "@type": "Person", 
      "name": "Holmes, E.C."
    }
  ], 
  "url": "https://zenodo.org/record/3668497", 
  "datePublished": "2019-05-18", 
  "version": "1.0.0", 
  "keywords": [
    "metagenomics", 
    "microbiome"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.3668497", 
  "@id": "https://doi.org/10.5281/zenodo.3668497", 
  "@type": "SoftwareSourceCode", 
  "name": "CCMetagen: comprehensive and accurate identification of eukaryotes and prokaryotes in metagenomic data"
}