The source code of the mOTU profiler is available on GitHub. Installation of the mOTU profiler and its dependencies can be performed manually using the conda package manager or by downloading the docker image.

Installation with Conda

The mOTU profiler and all its dependencies can be installed with Conda using only a single command:
conda install -c bioconda motus
For installation via the conda system, there is currently a known issue relating to the installation of SAMtools. In case you encounter problems with the conda installation, please install mOTUs2 via GitHub (see below).

Manual Installation

The alternative to Conda is the installation of the mOTU profiler and its dependencies by hand.

Dependencies

The mOTU profiler depends on BWA ≥ v0.7.15 for sequence alignment, SAMtools ≥ v1.5 to parse SAM files, Python ≥ v3.0.0 to execute the scripts and metaSNV = v1.0.3.

mOTU Profiler

The mOTU profiler can be downloaded from Github. Installation downloads the program, databases and test datasets:
git clone https://github.com/motu-tool/mOTUs_v2.git
cd mOTUs_v2
python setup.py
export PATH=`pwd`:$PATH
python test.py
A successful installation will print the following message:
------------------------------------------------------------------------------
|                  TEST MOTUS TOOL                    |
------------------------------------------------------------------------------

1-- ran setup.py: done

2-- Tools and versions:
- python: correct
- bwa: correct
- samtools: correct
- metaSNV: correct

3-- Taxonomy profiling test:
- Run motus (-v 1, only error messages):
- end motus call

Check resulting profile: correct

Docker

Bioconda is automatically building a Docker image that can be used to take advantage of the mOTU profiler without actually installing it:
docker pull quay.io/biocontainers/motus:2.0.0--py35_0

Using the mOTUs profiler

Three datasets were downloaded during installation. Execute the commands in the tutorials section to see how the mOTUs profiler is used.

Extending the mOTUs database

It is possible to extend the mOTUs database with genomes of interest. The code that performs the extension as well as a tutorial and example datasets can be found here.