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Updated: Apr 3, 2026

Targeted DNA Methylation Analysis by Next-generation Sequencing
Published on: February 24, 2015
RAMBO-K: Rapid and Sensitive Removal of Background Sequences from Next Generation Sequencing Data
Simon H Tausch1, Bernhard Y Renard2, Andreas Nitsche1
1Centre for Biological Threats and Special Pathogens, Robert Koch Institute, 13353, Berlin, Germany.
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/.
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