This is a remake of the original 16S pipeline developed with in the Genome Institute of Singapore, designed for Illumina shotgun sequencing of 16S rRNA amplicon sequences (Ong et al., 2013, PMID 23579286).

Running the pipeline

The pipeline is based on snakemake. The main program (S16.py) will write a config file (conf.json) and snakemake file (snake.make) in the given output directory. These are then used to call snakemake via qsub using the also created wrapper script snake.sh. The system will send an email to you upon completion (be it successful or not).

For help see S16.py --help.

Only upon successful completion the output directory will contain an empty file called COMPLETE.

Results (abundance tables and piecharts) can then be found in results subdirectory (see report.html there).

Steps involved

• Reads are first preprocessed (merging of multiple files, trimming etc.) with famas.
• Preprocessed reads are classified into 'unspecific', 'spike-in' and '16S', based on a BWA-MEM mapping against the original EMIRGE/ARB SSU database containing the spike-in (see ratios.txt for corresponding ratios).
• Only 16S sequences are used for reconstructing the full-length sequences with EMIRGE (Miller et al., 2011, PMID 21595876) or EMIRGE amplicon (Miller et al., 2013; PMID 23405248)
• Primers are clipped from the reconstructed sequences
• Clipped sequences are mapped with Graphmap against a preclustered version (99% OTU) of the Greengenes database for classification.
• Abundance-tables and piecharts are created in the results subdirectory of the output directory. Pairwise identity thresholds for the different taxonomi ranks are implemented as determined by Yarza et al. (2014; PMID 25118885).

Tip

If you want to first see what the pipeline would do, call S16.py with --no-run. Then check the created files (see above).

To print all commands that would be run, use:

snakemake -s snake.make --configfile conf.json -n -p

To get a graphical representation of the workflow, run (from the output directory):

snakemake -s snake.make --configfile conf.json --dag --forceall | dot -Tpdf > dag.pdf

and have a look at dag.pdf. Once you're satisfied just run bash snake.sh.

Setup

This is tuned towards an in-house setup. If you want to replicate it see the CONF variable in S16.py, which lists expected binaries and databases.