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Metagenomic binning suite

Latest Version: 0.3.4

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GroopM is a metagenomic binning toolset. It leverages spatio-temoral
dynamics to accurately (and almost automatically) extract genomes
from multi-sample metagenomic datasets.

GroopM is largely parameter-free. Use: groopm -h for more info.

See also:


Should be as simple as

pip install GroopM

Data preparation and running GroopM

Before running GroopM you need to prep your data. A typical workflow looks like this:

1. Produce NGS data for your environment across mutiple (3+) samples (spearated spatially or temporally or both).
2. Co-assemble your reads using Velvet or similar.
3. For each sample, map the reads against the co-assembly. GroopM needs sorted indexed bam files. If you have 3 samples then you will produce 3 bam files. I use BWA / Samtools for this.
4. Take your co-assembled contigs and bam files and load them into GroopM using 'groopm parse' saveName contigs.fa bam1.bam bam2.bam...
5. Keep following the GroopM workflow. See: groopm -h for more info.

Licence and referencing

Project home page, info on the source tree, documentation, issues and how to contribute, see

This software is currently unpublished but a manuscript is being prepared. Please contact me at m_dot_imelfort_at_uq_dot_edu_dot_au for more information about referencing this software.

Copyright © 2012 Michael Imelfort. See LICENSE.txt for further details.  
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GroopM- (md5) Source 2013-11-19 124KB
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