metator 0.1.7

A pipeline for binning metagenomic datasets from 3C data.

metaTOR

Metagenomic Tridimensional Organisation-based Reassembly - A set of scripts that streamline the processing and binning of metagenomic 3C datasets.

Installation

   pip3 install metator

or, to use the latest version:

   pip3 install -e git+https://github.com/koszullab/metator.git@master#egg=metator

Python 3.4 or later is required. A standalone version (no installation, just download/unzip/run) is also available, as well as a Python 2 version, but keep in mind that development will focus on the current branch.

Usage

metator {align|partition|annotation|binning} [parameters]

A metaTOR command takes the form metator action --param1 arg1 --param2 arg2 #etc.

There are four actions/steps in the metaTOR pipeline, which must be run in the following order:

• align : map paired-end reads on a preliminary assembly, then generate a network from detected contacts between DNA chunks.

• partition : perform the Louvain community detection algorithm many times to isolate chunks that consistently cluster together for binning purposes.

• annotation : run standard annotation software on the assembly (namely gene prediction and database comparison) to match with the bins.

• binning : match annotations to bins, extract bin genomes and subnetworks, build bin-local and global contact maps.

After the last step is completed there should be a set of bins, their relative enrichments in various gene categories, and the contact map of each bin.

There are a number of other, optional, miscellaneous actions:

• pipeline : check the environment is right, then run all four of the above actions sequentially. This can take a while.

• dependencies : download third party dependencies that are not available in most package managers.

• deploy : set up the environment and all dependencies for Ubuntu 14.04 and higher (run as root).

• version : display current version number.

• help : display this help message.

Please refer to the tutorial in order to quickly get the pipeline up and running on example data (or your own), and the metaTOR manual for detailed explanations on the parameters.

Requirements

• Python 3 with numpy, scipy, matplotlib, biopython and pysam libraries.
• bowtie2
• samtools
• hmmer and some HMM databases (such as these)
• prodigal
• louvain (original implementation)

Requirements can usually be installed with an OS's package manager. The requirements that cannot (namely prodigal, louvain and HMM databases) can be fetched with the following (The package may need to be run as a root depending on where the package is installed):

    metator dependencies

Containers

A dockerfile is also available if that is of interest. You may fetch the image by running the following:

    docker pull koszullab/metator

Additionally, a Singularity file is also available, courtesy of avilab. You may fetch the container this way:

    singularity pull shub://kosullab/metator

References

• Metagenomic chromosome conformation capture (meta3C) unveils the diversity of chromosome organization in microorganisms, Martial Marbouty, Axel Cournac, Jean-François Flot, Hervé Marie-Nelly, Julien Mozziconacci, and Romain Koszul, eLife, 2014
• Meta3C analysis of a mouse gut microbiome, Martial Marbouty, Lyam Baudry, Axel Cournac, Romain Koszul, 2015
• Scaffolding bacterial genomes and probing host-virus interactions in gut microbiome by proximity ligation (chromosome capture) assay, Martial Marbouty, Lyam Baudry, Axel Cournac, and Romain Koszul, Science Advances, 2017

Contact

Authors

• [e-mail]
• [e-mail]
• [e-mail]
• [e-mail]

Research lab

Spatial Regulation of Genomes (Institut Pasteur, Paris)