Format

Send to

Choose Destination
Bioinformatics. 2011 Jan 15;27(2):196-203. doi: 10.1093/bioinformatics/btq649. Epub 2010 Dec 1.

MTR: taxonomic annotation of short metagenomic reads using clustering at multiple taxonomic ranks.

Author information

1
Radboud University Nijmegen, Institute for Computing and Information Sciences, Nijmegen, The Netherlands. gori@cs.ru.nl

Abstract

MOTIVATION:

Metagenomics is a recent field of biology that studies microbial communities by analyzing their genomic content directly sequenced from the environment. A metagenomic dataset consists of many short DNA or RNA fragments called reads. One interesting problem in metagenomic data analysis is the discovery of the taxonomic composition of a given dataset. A simple method for this task, called the Lowest Common Ancestor (LCA), is employed in state-of-the-art computational tools for metagenomic data analysis of very short reads (about 100 bp). However LCA has two main drawbacks: it possibly assigns many reads to high taxonomic ranks and it discards a high number of reads.

RESULTS:

We present MTR, a new method for tackling these drawbacks using clustering at Multiple Taxonomic Ranks. Unlike LCA, which processes the reads one-by-one, MTR exploits information shared by reads. Specifically, MTR consists of two main phases. First, for each taxonomic rank, a collection of potential clusters of reads is generated, and each potential cluster is associated to a taxon at that rank. Next, a small number of clusters is selected at each rank using a combinatorial optimization algorithm. The effectiveness of the resulting method is tested on a large number of simulated and real-life metagenomes. Results of experiments show that MTR improves on LCA by discarding a significantly smaller number of reads and by assigning much more reads at lower taxonomic ranks. Moreover, MTR provides a more faithful taxonomic characterization of the metagenome population distribution.

AVAILABILITY:

Matlab and C++ source codes of the method available at http://cs.ru.nl/gori/software/MTR.tar.gz.

PMID:
21127032
PMCID:
PMC3018814
DOI:
10.1093/bioinformatics/btq649
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Silverchair Information Systems Icon for PubMed Central
Loading ...
Support Center