mosaicforecast on Biowulf

MosaicForecast is a machine learning method that leverages read-based phasing and read-level features to accurately detect mosaic SNVs (SNPs, small indels) from NGS data. It builds on existing algorithms to achieve a multifold increase in specificity.


Important Notes

Interactive job
Interactive jobs should be used for debugging, graphics, or applications that cannot be run as batch jobs.

Allocate an interactive session and run the program.
Sample session (user input in bold):

[user@biowulf]$ sinteractive --cpus-per-task=2 --mem=2G
salloc.exe: Pending job allocation 46116226
salloc.exe: job 46116226 queued and waiting for resources
salloc.exe: job 46116226 has been allocated resources
salloc.exe: Granted job allocation 46116226
salloc.exe: Waiting for resource configuration
salloc.exe: Nodes cn3144 are ready for job

[user@cn3144 ~]$ module load mosaicforecast
[user@cn3144 ~]$
Usage: python bam_dir output_dir ref_fasta input_positions(file format:chr pos-1 pos ref alt sample, sep=\t) min_dp_inforSNPs(int) Umap_mappability(bigWig file,k=24) n_threads_parallel sequencing_file_format(bam/cram)

1. Name of bam files should be "sample.bam" under the bam_dir, and there should be corresponding index files.
2. There should be a fai file under the same dir of the fasta file (samtools faidx input.fa).
3. The "min_dp_inforSNPs" is the minimum depth of coverage of trustworthy neaby het SNPs.
4. Bam file is preferred than cram file, as the program would run much more slowly if using cram format.

[user@cn3144 ~]$ mkdir mosaicforecast_test && cd mosaicforecast
[user@cn3144 ~]$ cp -r ${MOSAIC_TESTDATA:-none}/* .
[user@cn3144 ~]$ ./demo/ test_out \
                     /fdb/GATK_resource_bundle/b37-2.8/human_g1k_v37_decoy.fasta \
                     ./demo/test.input 20 2 bam
[user@cn3144 ~]$ exit
salloc.exe: Relinquishing job allocation 46116226
[user@biowulf ~]$

Batch job
Most jobs should be run as batch jobs.

Create a batch input file (e.g. For example:

#SBATCH --cpus-per-task=2
#SBATCH --mem=2G
#SBATCH --time=2:00:00
#SBATCH --partition=norm

set -e
module load mosaicforecast
cp -r ${MOSAIC_TESTDATA:-none}/* .
cp -r ${MOSAIC_MODEL:-none}/* .
Prediction.R demo/test.SNP.features models_trained/250xRFmodel_addRMSK_Refine.rds Refine test.SNP.predictions

Submit the job:

Swarm of Jobs
A swarm of jobs is an easy way to submit a set of independent commands requiring identical resources.

Create a swarmfile (e.g. job.swarm). For example:

       Prediction.R demo/test.SNP.features models_trained/250xRFmodel_addRMSK_Refine.rds Refine SNP.predictions   
       Prediction.R demo/test.DEL.features models_trained/deletions_250x.RF.rds Phase DEL.predictions


Submit this job using the swarm command.

swarm -f job.swarm [-g #] --module mosaicforecast
-g # Number of Gigabytes of memory required for each process (1 line in the swarm command file)
--module Loads the module for each subjob in the swarm