caravagnalab / tumourevo

Analysis pipleine to model tumour clonal evolution from WGS data (driver annotation, quality control of copy number calls, subclonal and mutational signature deconvolution)

tumourevo

Analysis pipleine to model tumour clonal evolution from WGS data (driver annotation, quality control of copy number calls, subclonal and mutational signature deconvolution)

tumourevo's Issues

Add full path inside the module to save outputs (allowing publication in publishDir)

Upload existing nf-core modules/workflows

Add the following modules or subworkflows to a local/modules or local/subworkflows directory:

• VEP
• mpileup
• vcf2maf

Check both https://nf-co.re/subworkflows and https://nf-co.re/modules, considering that some modules may already exist as suboworkflows and vice-versa.

Variant Annotation

• Plug nf-core/vcf_annotate_ensemblvep subworkflow in correctly
• Add --SingleLetterAA flag as task.args (e.g. https://github.com/nf-core/taxprofiler/blob/1.1.8/conf/modules.config)
• Run only if vcfs are not already annotated
• check ensemble_vep_download module for running online

Convert all metadata input to string to avoid problems with join

Driver Analysis

Driver Analysis is a subworkflow that does:

• Global selection analysis (dndsCV)
• Identification of genes driving positive/negative selection (dndsCV)
• Identification of mutations with high immunogenicity (SOPRANO)

save the output of the tools to files and flags mutations in the mutation table accordingly.
Possible flags:

• known driver (from a user defined list of drivers e.g. IntoGen) (boolean)
• under_positive_selection (from dndsCV with user-defined significancy threshold) (boolean)
• under_negative_selection (from dndsCV with user-defined significancy threshold) (boolean)
• immunogenic (boolean)
• quantities (from the various table) (integer/float/string)

Test workflow

Set-up single module level tests using nf-test.

• Generate template for the simplest module (annotate_driver) @tucano :
  • Switch to external R script and rely on nextflow template

Subclonal Deconvolution

• Mobster and VIBER

  • Filter out non-diploid mutations

• Pyclone

  • Add full path inside the module to save outputs (allowing publication in publishDir)

• ctree

  • move to meta and fix updates

• Use meta tuple as input of the modules

  • Find a way to transpose elements inside the meta tuple to switch from multi to single sample

• Generate config file

• Drop single_sample/multi_sample modeality option and use flag e.g. --remove_tail once,all,never

Signatures Deconvolution

• SigProfiler
  • Finalise dockerfile with all required modules related to SigProfiler (e.g. Extractor, MatrixGenerator etc.)
• SparseSignatures

Genome interpreter

Generate summary results object with the following features:

• Sample-wise information:

  • Driver mutations with selection score
  • Mutation rate
  • Clone-tree structure
    • CCF for each clone
    • Number of mutations for each clone
  • Exposure distribution of each clone to signatures
    • SparseSignatures:: sigAssignmentLasso() (https://rdrr.io/bioc/SparseSignatures/man/sigAssignmentLasso.html) using subclones as individual samples

• Mutation-wise information:

  • Karyotype
  • Assignment to single-sample cluster
  • Assignment to multi-sample cluster
  • Assignment to mutational signature
  • Selection score (dnds fashion)

• Patient-wise information:

  • Sample tree (phylogeny)
  • Muller plot object

Test dataset

Generate test dataset from Sarek test bam files (two patients, two tumour samples + normal) using Sarek pipeline in two conditions:

• Solve issue concerning Sarek recalibration step
• Multi-sample variant calling (Mutect2)
• Single-sample variant calling

Dataset for testing - three patients, with drivers, try single chromosome (if not enough add more):

• One patient going to the lifter (with at least N private mutations)
• One patient not going to the lifter
• One patient that should go but no input BAM files provided
• One patient with two samples, one of which contaminated (thrown away by TINC)

General Architecture

• Metadata propagation here
  • Include plugin nf-validation (https://github.com/nextflow-io/nf-validation)
  • Write schema_input.json in assets (e.g. Sarek https://github.com/nf-core/sarek/tree/master/assets)
  • From samplesheet parsing, return a boolean for lifter usage (e.g. https://github.com/nf-core/sarek/blob/master/subworkflows/local/samplesheet_to_channel/main.nf)
• Development of single modules/relying on scripts
• Output management for final assembly
• Reorganise config files:
  • Build config file for each module with publishDir etc. (like https://github.com/nf-core/sarek/blob/master/conf/modules/ascat.config)
    • ensemblevep
    • formatter (subworkflow)
    • QC
      • CNAqc
      • TINC
    • subclonal deconvolution
      • mobster
      • viber
      • pyclone
      • ctree
    • signatures deconvolution
      • sparsesigs
      • sigprofiler
  • Build a config with resources for each module with tag (eg process_medium etc. https://github.com/nf-core/sarek/blob/b5b766d3b4ac89864f2fa07441cdc8844e70a79e/conf/base.config)