CCMetagen: comprehensive and accurate identification of eukaryotes and prokaryotes in metagenomic data

Vanessa R. Marcelino*, Philip Thomas Lanken Conradsen Clausen, Jan P. Buchmann, Michelle Wille, Jonathan R. Iredell, Wieland Meyer, Ole Lund, Tania C. Sorrell, Edward C. Holmes

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

There is an increasing demand for accurate and fast metagenome classifiers that can not only identify bacteria, but all members of a microbial community. We used a recently developed concept in read mapping to develop a highly accurate metagenomic classification pipeline named CCMetagen. The 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.
Original languageEnglish
Article number103
JournalGenome Biology (Online Edition)
Volume21
Number of pages15
ISSN1474-7596
DOIs
Publication statusPublished - 2020

Keywords

  • Microbiome
  • Metagenomic classifier
  • ConClave sorting
  • Fungi

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