Documentation for SCOUT cohort

Workflow

For every SPN, the following steps are requested:

1. ProCESS simulation: perform simulation of tumour growth, sampling and mutation engine set up according to genomics information reported in SCOUT and the instruction in the SCOUT section;

2. sequencing simulation: perform ProCESS sequencing of all 12 coverage-purity combinations (+ normal sample) following the step reporting in the build cohort section

3. generate report for each coverage-purity combination according to report generation section;

4. run nf-core/sarek for each coverage-purity combination. In particular:

   4.1 Mapping and preprocessing of normal sample;

   4.2 Mapping and prepocessing of coverage-purity combination (considered as different runs)

   4.3 Variant calling of coverage-purity combinations

5. run nf-core/tumourevo on nf-core/sarek results.

6. perform validation of nf-core/sarek results by comparing:

   6.1 Variant Allele Frequency of called somatic mutations (Strelka, Mutect2) vs Variant Allele Frequency of ProCESS ground truth mutations;

   6.2 Variant Allele Frequency of called germline mutations (Haplotypecaller) vs Variant Allele Frequency of ProCESS ground truth mutations;

   6.3 Purity and ploidy estimates from ASCAT given the set purity;

   6.4 Segments and karyotypes from ASCAT vs phylo_forest$get_bulk_allelic_fragmentation of ProCESS ground truth CNAs.

7. perform validation of nf-core/tumourevo results by comparing:

   7.1 Driver mutations;

   7.2 Clonal and subclonal clusters given the set ProCESS samples composition;

   7.3 Signature exposure vs phylo_forest$get_exposures()

8. perform plots for resource usage.

Summary table

step	sub-step	main script	output file	expected n of files
🟢 races simulation	simulate tissue	0_sim_tissue.R	sample_forest.sff snapshot	2
-	set mutation engine	1_mut_engine.R	phylo_forest.sff cna.rds	1+n
🔴 build cohort	sequencing tumour	build_cohort.py	purity_{}/../seq_results_SPN{}_t{}.rds	3x40
-	sequencing normal	-	purity_1/../seq_results_SPN{}_n{}.rds../	1x6
-	merginig tumour	-	purity_{}/../seq_results_merged_SPN{}_{}x.rds	3x4
-	merginig normal	-	purity_1/seq_results_merged_SPN{}_30x.rds	1
-	fastq tumour generation	-	purity_{}/t{}_Sample_1.{R1,R2}.fastq.gz	3x40x2xn
-	fastq normal generation	-	purity_1/n{}_normal_sample.{R1,R2}.fastq.gz	6x2
🔴 sarek	mapping normal sample	sarek_mapping_normal.sh	normal_sample.recal.cram	1
-	mapping tumour samples	sarek_mapping_{}x_{}p.sh	{}x_{}p/SPN{}_S{}.recal.cram	12xn
-	mapping tumour samples	sarek_mapping_{}x_{}p.sh	{}x_{}p/SPN{}_S{}.recal.cram	12xn
-	variant calling strelka tumour samples	sarek_variant_calling_{}x_{}p.sh	{}x_{}p/SPN{}_S{}.vcf	12xn
-	variant calling mutect2 tumour samples	sarek_variant_calling_{}x_{}p.sh	{}x_{}p/SPN{}_S{}.vcf	12
-	variant calling haplotypecaller tumour samples	sarek_mapping_normal.sh	SPN{}_normal_sample.vcf	1
-	variant calling ascat tumour samples	sarek_variant_calling_{}x_{}p.sh	{}x_{}p/SPN{}_S{}.txt	12xn
🟠 tumourevo	drivers	``	{}x_{}p/SPN{}_S{}.rds	12x2xn
-	subclonal	``	{}x_{}p/SPN{}_S{}.rds	12x2xn
-	signature	``	{}x_{}p/SPN{}.rds	12x2

Note

n referes to the number of samples of each SPN

🟢: low resource usage

🟠: medium resource usage

🔴: high resource usage

Folder structure

For this project we will have a data folder where all the resulting files will be stored and a copy of the remote repository. This is the expected structure of the data folder for each SPN:

SCOUT/SPN{id}
    ├── races
    |   ├── sample_forest.sff
    |   ├── phylo_forest.sff
    |   ├── SPN{id}
    |   └── cna_data
    |       └── <sample>_cna.rds            
    ├── sarek
    |   ├── normal_sample
    |   |    ├── multiqc
    |   |    ├── pipeline_info
    |   |    ├── preprocessing
    |   |    │   ├── markduplicates
    |   |    │   |   └── <sample>
    |   |    │   ├── recal_table
    |   |    │   |   └── <sample>
    |   |    │   └── recalibrated
    |   |    │       └── <sample>
    |   |    └── variant_calling
    |   |        └── haplotypecaller
    |   |            └── <sample>                  
    |   └── {coverage}x_{purity}p
    |            ├── multiqc
    |            ├── pipeline_info
    |            ├── preprocessing
    |            │   ├── markduplicates
    |            │   |   └── <sample>
    |            │   ├── recal_table
    |            │   |   └── <sample>
    |            │   └── recalibrated
    |            │       └── <sample>
    |            └── variant_calling
    |                ├── mutect2
    |                |   └── <patient>
    |                └── strelka
    |                   └── <sample>
    ├──tumourevo
    |   └── {coverage}x_{purity}p
    |       └── {variant_caller}_ascat
    |           ├── variant_annotation
    |           |   └── <sample>
    |           ├── signature_deconvolution
    |           |   ├── SparseSignatures
    |           |   └── SigProfiler
    |           └── subclonal_deconvolution
    |               ├── viber
    |               ├── ctree
    |               ├── pyclone                    
    |               └── mobster
    ├── validation
    |   └── {coverage}x_{purity}p
    |       ├── sarek
    |       |   ├── somatic_mutations
    |       │   |   ├── strelka
    |       │   |   └── mutect2
    |       |   ├── germline_mutations
    |       │   |   └── haplotypecaller
    |       │   └── copy_number
    |       │       └── ascat
    |       └── tumourevo
    |           └── {variant_caller}_ascat
    |               ├── drivers
    |               ├── signature_deconvolution
    |               └── subclonal_deconvolution
    ├── report
    |   └── Report_SPN{id}_{coverage}x_{purity}p.html
    └── resources
        └──