FOCUS: An alignment-free model to identify organisms in metagenomes using non-negative least squares

Genivaldo Gueiros Z. Silva, Daniel A. Cuevas, Bas E. Dutilh, Robert A. Edwards

Research output: Contribution to journalArticle

43 Citations (Scopus)

Abstract

One of the major goals in metagenomics is to identify the organisms present in a microbial community fromunannotated shotgun sequencing reads. Taxonomic profiling has valuable applications in biological and medical research, including disease diagnostics. Most currently available approaches do not scale well with increasing data volumes, which is important because both the number and lengths of the reads provided by sequencing platforms keep increasing. Here we introduce FOCUS, an agile composition based approach using non-negative least squares (NNLS) to report the organisms present in metagenomic samples and profile their abundances. FOCUS was tested with simulated and real metagenomes, and the results show that our approach accurately predicts the organisms present in microbial communities. FOCUS was implemented in Python. The source code and web-sever are freely available at http://edwards.sdsu.edu/FOCUS.

Original languageEnglish
Article numbere425
Number of pages13
JournalPeerJ
Volume2014
Issue number1
DOIs
Publication statusPublished - 5 Jun 2014
Externally publishedYes

Bibliographical note

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

Keywords

  • K-mer
  • Metagenomes
  • Modeling

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