Manual

• Introduction
  • Dependencies
  • Docker images
• How to run SomaticSeq
  • SomaticSeq Training Mode
  • SomaticSeq Prediction Mode
  • Consensus Mode
• Use SomaticSeq as a Python library
  • somaticseq.somaticseq modules
    • Module: run_somaticseq
    • Module: somatic_vcf2tsv and single_sample_vcf2tsv
    • Module: SSeq_tsv2vcf
  • somaticseq.utilities modules
    • Module: split_Bed_into_equal_regions
    • Module: lociCounterWithLabels
• The step-by-step SomaticSeq Workflow
  • Apply inclusion and exclusion regions
  • Combine the call sets
  • Convert the VCF file into TSV file
  • Model Training or Mutation Prediction
• To run the dockerized somatic mutation callers
  • Location
  • Requirements
  • Example commands
    • Single-threaded Jobs
    • Multi-threaded Jobs
    • SomaticSeq Training
    • SomaticSeq Prediction
    • Parameters
    • What does the single-threaded command do
    • What does the multi-threaded command do
• Use BAMSurgeon to create training data
  • Requirements
  • Three scenario to simulate somatic mutations
    • When you have sequencing replicates of normal samples
    • This example mimicks DREAM Challenge
    • Merge and then split the input tumor and normal BAM files
  • Parameters and Options
    • –merge-bam / –split-bam / –indel-realign
  • To create SomaticSeq classifiers
• Release Notes
• Contact Us