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SPHINX- An algorithm for taxonomic binning of metagenomic sequences
| Content Provider | CiteSeerX |
|---|---|
| Author | Monzoorul Haque, M. Ghosh, Tarini Shankar Singh, Nitin Kumar Sharmila, S. |
| Abstract | Motivation: Compared to 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 data sets. The motivation was to develop a binning approach that can analyze metagenomic data sets as rapidly as composition based approaches, but nevertheless has the accuracy and specificity of alignment based algorithms. This paper 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 data sets 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 to results obtained using alignment based algorithms. Availability: A web-server for the SPHINX algorithm is available at |
| File Format | |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
