mOTUs profiler

The mOTUs profiler is a computational tool that estimates relative abundance of known and currently unknown microbial community members using metagenomic shotgun sequencing data.

Check the wiki for more information.

Pre-requisites

The mOTU profiler requires:

• Python 3 or Python 2.7 (or higher)
• the Burrow-Wheeler Aligner v0.7.15 or higher (bwa)
• SAMtools v1.5 or higher (link)

In order to use the command snv_call you need:

• metaSNV v1.0.3, available also on bioconda (we assume metaSNV.py to be in the system path)

Check installation wiki to see how to install the dependencies with conda.

Installation

git clone https://github.com/motu-tool/mOTUs_v2.git
cd mOTUs_v2
python setup.py
python test.py
export PATH=`pwd`:$PATH

Note: in the following examples we assume that the python script motus is in the system path.

Simple examples

Here is a simple example on how to obtain a taxonomic profiling from a raw read file:

motus profile -s metagenomic_sample.fastq > taxonomy_profile.txt

You can separate the previous call as:

motus map_tax -s metagenomic_sample.fastq -o mapped_reads.sam
motus calc_mgc -i mapped_reads.sam -o mgc_ab_table.count
motus calc_motu -i mgc_ab_table.count > taxonomy_profile.txt
rm mapped_reads.sam mgc_ab_table.count

The use of multiple threads (-t) is recommended, since bwa will finish faster. Here is an example with Paired-End reads:

motus profile -f for_sample.fastq -r rev_sample.fastq -s no_pair.fastq -t 6 > taxonomy_profile.txt

You can merge taxonomy files from different samples with mOTU merge:

motus profile -s metagenomic_sample_1.fastq -o taxonomy_profile_1.txt
motus profile -s metagenomic_sample_2.fastq -o taxonomy_profile_2.txt
motus merge -i taxonomy_profile_1.txt,taxonomy_profile_2.txt > all_sample_profiles.txt

You can profile samples that have been sequenced through different runs:

motus profile -f sample1_run1_for.fastq,sample1_run2_for.fastq -r sample1_run1_rev.fastq,sample1_run2_rev.fastq -s sample1_run1_single.fastq > taxonomy_profile.txt