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bbglab/deepCSA: Output

Introduction

This document describes the output produced by the pipeline.

Pipeline overview

The pipeline is built using Nextflow and processes data using the following steps:

Directory Structure

The directory structure listed below will be created in the results directory after the pipeline has finished. The structure captures the maximum diversity of created outputs, but when only certain run options are turned on, not all directories will be generated. All paths are relative to the top-level results directory.

{outdir}
├──absolutemutabilities
├──absolutemutabilitiesgloballoc
├──annotatedepths
├──clean_germline_somatic
├──clean_somatic
├──computematrix
├──computeprofile
├──createpanels
│   ├── consensus
│   │   └── <region_type>.consensus.bed
│   │   └── <region_type>.consensus.tsv
│   ├── captured
│   │   └── <region_type>.captured.bed
│   │   └── <region_type>.captured.tsv
│   └── sample
│       └── <region_type>.<sample>.bed
│       └── <region_type>.<sample>.tsv
├──customannotation
├──customprocessing
├──customprocessingrich
├──depthssummary
├──dna2proteinmapping
├──domainannotation
├──expandregions
├──filterexons
├──germline_somatic
├──groupgenes
├──indels
├──matrixconcatwgs
├──multiqc
├──mutability
├──mutatedcellsfromvafam
├──mutatedgenomesfromvafam
├──mutrate
├──muts2sigs
├──omega
│   ├── preprocessing
│   │   └── syn_muts.<sample>
│   │   └── mutabilities.<sample>
│   └── output_mle.<sample>.tsv
├──omegagloballoc
│   ├── preprocessing
│   │   └── syn_muts.<sample>
│   │   └── mutabilities.<sample>
│   └── output_mle.<sample>.tsv
├──oncodrive3d
│   ├── run
│       └── <sample>
│   └── plot
│       └── <sample>
├──oncodrivefmlsnvs
├──pipeline_info
├──plotmaf
├──plotneedles
│   └── <sample>
│       └── <gene-sample needles>
├──plotselection
├──plotsomaticmaf
├──postprocessveppanel
├──signatures_hdp
│   └── output.<region_type>
│       └── <sample>
├──sigprobs
├──sigprofilerassignment
│   └── output.<region_type>
│       └── <sample>
├──sitecomparison
├──sitecomparisongloballoc
├──sitecomparisongloballocmulti
├──sitecomparisonmulti
├──sitesfrompositions
├──sumannotation
├──synmutrate
├──synmutreadsdensity
└──table2group
work/
.nextflow.log

Input and configuration

See Usage docs for extensive explanation on required inputs and format. Including documentation on parameters to run on for 4 different suggested running modes.

Depth analysis

Key role

  • Computation of depth per sample for each specific position Most analysis may be influenced by sequencing depth, it is essential to correct for these values.

  • Definition of regions to analyze Only genomic areas that have been properly covered across samples will be used for the analysis.

Note 1: There is a depth difference between the depth reported in the files in the annotated depths directory and the values of depth reported in each of the mutations. This difference is because we do not count Ns when computing th depth of specific mutations. This means that the values of VAF are computed with N-discounted depth, while other metrics are not.

Detailed explanation of depthssummary depths versions

In this directory you will find different versions of TSVs and PDFs summarizing the depths of the samples/genes sequenced.

Each of the versions provides slightly different information, as you can see in the image below:

depths summary slide

  • exons contains the average depth in all the exonic regions sequenced in the genome no matter which minimum consensus coverage was reached.
  • exons_cons contains the average depth in the exonic regions sequenced in the genome to a minimum consensus depth threshold. (only exons in the well covered regions)
  • all_cons contains the average depth of all sequenced regions of the genome that are well covered across the samples in the cohort, without any distinction of exons/introns/others.

We will work on a better representation of the different metrics of depth so that is it more understandable, but for now we include this schematic and brief explanations.

Reach out if you have more questions!

Outputs

  • sitesfrompositions
  • postprocessveppanel
  • createpanels
  • annotatedepths
  • depthssummary

Optional:

  • dna2proteinmapping
  • domainannotation
  • customprocessing
  • customprocessingrich

Mutation preprocessing

Key role

  • VCF annotation: Annotate mutations with Ensembl VEP.
  • VCF to MAF conversion: Convert VCFs to MAF, define VAF, and merge with annotation.
  • Custom region annotation: Allow user to define different consequence types for specific regions.
  • Hotspot annotation: Add known hotspots to mutation annotation.
  • Filtering:
    • Filter mutations at the sample level (e.g., VAF distortion).
    • Filter at the cohort level (e.g., other_sample_SNP, repetitive_variant, not_covered, not_in_exons).
  • Blacklist mutations if activated (see assets for example).
  • Downsample mutations if activated.

Outputs

  • sumannotation
  • customannotation
  • germline_somatic
  • clean_somatic
  • clean_germline_somatic

Basic analysis

Key role

  • Mutation density computation Correct the number of mutations observed by the number of sequenced nucleotides.

  • Mutational profile computation Capture the mutation probability of each trinucleotide. Represent it in three different normalization conditions.

Outputs

  • computematrix
  • computeprofile
  • mutrate

Intermediate outputs

Key role

  • Matrix concatenation Combine WGS-renomralized matrices for mutational signature analysis.

  • Mutability calculation Compute relative mutabilities using depths and mutational profile.

  • Choose synonymous mutation rates for downstream analysis.

Outputs

  • matrixconcatwgs
  • mutability
  • synmutrate
  • synmutreadsdensity

Positive selection

Key role

  • Compute multiple positive selection metrics This is done at the cohort-level, but also for each sample or group of samples.

  • OncodriveFML: Detects functional impact bias in observed mutations.

  • Oncodrive3D: Identifies 3D protein regions with mutation clustering, using relative mutabilities and raw VEP annotation.

  • Omega: dN/dS-based, quantifies selection pressure in defined regions (genes, exons, domains, hotspots, etc.).

  • Indels: Analysis of indel selection.

Outputs

  • omega
  • omegagloballoc
  • oncodrive3d
  • oncodrivefmlsnvs
  • indels

Site selection metrics

Key role

  • Compute absolute mutabilities for each position.

  • Compare the observed number of mutations per site to the expected number of mutations and estimate a site selection value.

Outputs

  • absolutemutabilities

  • absolutemutabilitiesgloballoc

  • sitecomparison

  • sitecomparisongloballoc

  • sitecomparisongloballocmulti

  • sitecomparisonmulti

Additional clonal structure metrics

Key role

  • VAF-based definition of the number of mutated genomes.

Outputs

  • mutatedcellsfromvafam
  • mutatedgenomesfromvafam

Mutational signatures

Key role

  • Signature assignment: Use SigProfilerAssignment with optional custom signatures.
  • HDP: Hierarchical Dirichlet Process for signature extraction.
  • (Pending) Signature extraction: SigProfilerExtractor support.

Outputs

  • signatures_hdp
  • sigprofilerassignment
  • sigprobs
  • muts2sigs

Plotting functionalities

Key role

  • Plotting basic statistics of numbers and distribution of mutations in genes.

  • Optionally think on adding more plots.

Outputs

  • plotmaf
  • plotneedles
  • plotselection
  • plotsomaticmaf

Additional outputs

Key role

  • Definition of groups, expanded regions and other metrics related with the full pipeline execution.

Outputs

  • table2group
  • groupgenes
  • expandregions
  • filterexons
  • multiqc
  • pipeline_info