Journal
BIOINFORMATICS
Volume 27, Issue 1, Pages 22-30Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btq608
Keywords
-
Ask authors/readers for more resources
Motivation: Compared with composition-based binning algorithms, the binning accuracy and specificity of alignment-based binning algorithms is significantly higher. However, being alignment-based, the latter class of algorithms require enormous amount of time and computing resources for binning huge metagenomic datasets. The motivation was to develop a binning approach that can analyze metagenomic datasets as rapidly as composition-based approaches, but nevertheless has the accuracy and specificity of alignment-based algorithms. This article describes a hybrid binning approach (SPHINX) that achieves high binning efficiency by utilizing the principles of both 'composition'- and 'alignment-based binning algorithms. Results: Validation results with simulated sequence datasets indicate that SPHINX is able to analyze metagenomic sequences as rapidly as composition-based algorithms. Furthermore, the binning efficiency (in terms of accuracy and specificity of assignments) of SPHINX is observed to be comparable with results obtained using alignment-based algorithms.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available