SomaticSeq: An ensemble approach to accurately detect somatic mutations

• Detailed documentation is included in the package. It's located in docs/Manual.pdf. Quick guide can be found here.
• SomaticSeq's open-access paper: Fang LT, Afshar PT, Chhibber A, et al. An ensemble approach to accurately detect somatic mutations using SomaticSeq. Genome Biol. 2015;16:197.
• Feel free to report issues and/or ask questions at the Issues page. You may also email Li Tai Fang at li_tai.fang@roche.com.

The following command is an example SomaticSeq command after mutation caller jobs are complete:

• If you're searching for pipelines to run those individual somatic mutation callers, consider our dockerized somatic mutation pipelines.

$somaticseq/SomaticSeq.Wrapper.sh \
--output-dir       /PATH/TO/RESULTS/SomaticSeq_MVSDULPK \
--genome-reference /PATH/TO/GRCh38.fa \
--tumor-bam        /PATH/TO/HCC1395.bam \
--normal-bam       /PATH/TO/HCC1395BL.bam \
--dbsnp            /PATH/TO/dbSNP.GRCh38.vcf \
--cosmic           /PATH/TO/COSMIC.v77.vcf \
--mutect2          /PATH/TO/RESULTS/MuTect2.vcf \
--varscan-snv      /PATH/TO/RESULTS/VarScan2.snp.vcf \
--varscan-indel    /PATH/TO/RESULTS/VarScan2.indel.vcf \
--sniper           /PATH/TO/RESULTS/SomaticSniper.vcf \
--vardict          /PATH/TO/RESULTS/VarDict.vcf \
--muse             /PATH/TO/RESULTS/MuSE.vcf \
--lofreq-snv       /PATH/TO/RESULTS/LoFreq.somatic_final.snvs.vcf.gz \
--lofreq-indel     /PATH/TO/RESULTS/LoFreq.somatic_final.indels.vcf.gz \
--scalpel          /PATH/TO/RESULTS/Scalpel.vcf \
--strelka-snv      /PATH/TO/RESULTS/Strelka/results/variants/somatic.snvs.vcf.gz \
--strelka-indel    /PATH/TO/RESULTS/Strelka/results/variants/somatic.indels.vcf.gz \
--inclusion-region /PATH/TO/RESULTS/captureRegion.bed \
--exclusion-region /PATH/TO/RESULTS/blackList.bed

• For all those input VCF files, either .vcf or .vcf.gz are acceptable.
• You must make sure all the input files (i.e., VCF, BAM, FASTA, etc.) are sorted identically. Otherwise, the results would not be valid, because the program does not check for proper ordering.
• Additional parameters for training/prediction:
  • --truth-snv: if you have ground truth VCF file for SNV
  • --truth-indel: if you have a ground truth VCF file for INDEL
  • --ada-r-script: $somaticseq/r_scripts/ada_model_builder_ntChange.R to build classifiers (.RData files), if you have ground truths supplied.
  • --classifier-snv: classifier (.RData file) previously built for SNV
  • --classifier-indel: classifier (.RData file) previously built for INDEL
  • --ada-r-script: $somaticseq/r_scripts/ada_model_predictor.R to use the classifiers specified above to make predictions
• Do not worry if Python throws the following warning. This occurs when SciPy attempts a statistical test with empty data, e.g., z-scores between reference- and variant-supporting reads will be NaN if there is no reference read at a position.

    RuntimeWarning: invalid value encountered in double_scalars
    z = (s - expected) / np.sqrt(n1*n2*(n1+n2+1)/12.0)
  

Pipelines and Workflows

• We have dockerized pipeline that runs all the somatic mutation callers and SomaticSeq at utilities/dockered_pipelines.
• We also have dockerized pipeline for in silico mutation spike in at utilities/dockered_pipelines/bamSimulator. This pipeline is based on BAMSurgeon. It can be used to create training set to build SomaticSeq classifiers.
• Those two pipelines are also ported to singularity at utilities/singularities, although they may not be as extensively tested or optimized as the dockered ones. Read the pages at the dockered pipelines for descriptions and how-to's.
• A Snakemake workflow to run the somatic mutation callers and SomaticSeq, created by Afif Elghraoui, is at utilities/snakemake.
• The limited pipeline to generate BAM files based on GATK's best practices is at utilities/dockered_pipelines/alignments (dockers only, no singularity yet).

For a quick description of SomaticSeq, you may watch this 8-minute video: