🚧 The SOP is not fully implemented here. See the Langille Lab's wiki for the most up-to-date version.

The Langille Lab's metagenomic SOP, implemented as a WDL workflow.

This workflow is designed to be run on a Unix-based system.

To ease the installation of dependencies, we use conda to manage the execution environment:

$ conda env create
$ source activate mgs_sop

If you'd like to install the tools manually, see the environment.yml file for the project dependencies.

The workflow relies on several user supplied inputs to complete its tasks. Before running the workflow, you'll want to copy the input template and populate it with the details for your project and environment. For example:

$ cp inputs.template.json inputs.json

Then open the file with your preferred text editor and fill in the values. Some values describe the location of required databases (see following section).

A mapping database for screening reads can be downloaded from the Langille Lab (Note: the file is ~3.5GB):

$ curl \
    http://kronos.pharmacology.dal.ca/public_files/GRCh38_PhiX_bowtie2_index.tar.gz \
    > /tmp/GRCh38_PhiX_bowtie2_index.tar.gz
$ tar xvzf GRCh38_PhiX_bowtie2_index.tar.gz -C databases
$ rm /tmp/GRCh38_PhiX_bowtie2_index.tar.gz

# Copy and paste the absolute path of the database directory in your
# inputs.json. If on Linux, you can get the full path by:
$ readlink -f databases/GRCh38_PhiX_bowtie2_index/

Run the workflow with Cromwell (assumes the populated inputs template was named inputs.json):

$ cromwell run workflow.wdl --inputs inputs.json

Test data can be obtained from NCBI using the SRA Toolkit. The following commands will download a small sample set of FASTQs (from an HMP project, accessible via NCBI with project accession PRJNA46333:

$ fastq-dump \
    --readids \
    --split-files \
    --maxSpotId 10 \
    --outdir tests/fastq/ \
    SRR3644404

Once the test data has been downloaded, run the workflow with the test input file:

$ cromwell run workflow.wdl --inputs tests/inputs.test.json