کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
2817762 | 1160011 | 2012 | 7 صفحه PDF | دانلود رایگان |
Phylogenetic assignment of individual sequence reads to their respective taxa, referred to as ‘taxonomic binning’, constitutes a key step of metagenomic analysis. Existing binning methods have limitations either with respect to time or accuracy/specificity of binning. Given these limitations, development of a method that can bin vast amounts of metagenomic sequence data in a rapid, efficient and computationally inexpensive manner can profoundly influence metagenomic analysis in computational resource poor settings. We introduce TWARIT, a hybrid binning algorithm, that employs a combination of short-read alignment and composition-based signature sorting approaches to achieve rapid binning rates without compromising on binning accuracy and specificity. TWARIT is validated with simulated and real-world metagenomes and the results demonstrate significantly lower overall binning times compared to that of existing methods. Furthermore, the binning accuracy and specificity of TWARIT are observed to be comparable/superior to them. A web server implementing TWARIT algorithm is available at http://metagenomics.atc.tcs.com/Twarit/
► TWARIT uses a novel compositional signature sorting approach to achieve binning.
► TWARIT classifies reads from known and unknown genomes in two distinct phases.
► TWARIT is approximately two orders of magnitude faster than alignment-based tools.
► TWARIT can classify millions of metagenomic reads within a few hours.
► TWARIT has binning accuracy and specificity comparable to alignment-based methods.
Journal: Gene - Volume 505, Issue 2, 1 September 2012, Pages 259–265