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RAMBO-K: Rapid and Sensitive Removal of Background Sequences from Next Generation Sequencing Data.

ABSTRACT:

Background

The assembly of viral or endosymbiont genomes from Next Generation Sequencing (NGS) data is often hampered by the predominant abundance of reads originating from the host organism. These reads increase the memory and CPU time usage of the assembler and can lead to misassemblies.

Results

We developed RAMBO-K (Read Assignment Method Based On K-mers), a tool which allows rapid and sensitive removal of unwanted host sequences from NGS datasets. Reaching a speed of 10 Megabases/s on 4 CPU cores and a standard hard drive, RAMBO-K is faster than any tool we tested, while showing a consistently high sensitivity and specificity across different datasets.

Conclusions

RAMBO-K rapidly and reliably separates reads from different species without data preprocessing. It is suitable as a straightforward standard solution for workflows dealing with mixed datasets. Binaries and source code (java and python) are available from http://sourceforge.net/projects/rambok/.

SUBMITTER: Tausch SH

PROVIDER: S-EPMC4574938 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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RAMBO-K: Rapid and Sensitive Removal of Background Sequences from Next Generation Sequencing Data.

Tausch Simon H SH Renard Bernhard Y BY Nitsche Andreas A Dabrowski Piotr Wojciech PW

PloS one 20150917 9

<h4>Background</h4>The assembly of viral or endosymbiont genomes from Next Generation Sequencing (NGS) data is often hampered by the predominant abundance of reads originating from the host organism. These reads increase the memory and CPU time usage of the assembler and can lead to misassemblies.<h4>Results</h4>We developed RAMBO-K (Read Assignment Method Based On K-mers), a tool which allows rapid and sensitive removal of unwanted host sequences from NGS datasets. Reaching a speed of 10 Megaba ...[more]

PMID: 26379285

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