CINSignatureCellLines

Code base used to generate copy number signatures from pan-cancer cell line SNP6.0 array data used to generate copy number signatures as part of the publication "A pan-cancer compendium of chromosomal instability"

Final absolute copy number profiles (hg19) for these cell lines can be found here. Copy number signatures can be easily generated from these profiles using the CINSignatureQuantification package.

Reproducing cell line data

Setup

Clone this git repository and cd into the directory

git clone https://github.com/markowetzlab/CINSignatureCellLines
cd CINSignatureCellLines

Install the conda environment

conda create --name CINSignatureCellLines --file conda_env.txt
conda activate CINSignatureCellLines

Run the setup bash script to install remote resources and reference files

./scripts/setup_dir.sh

Download external data

Edit the line specifying the access credentials for the restricted access dataset EGAD00010000644. Remove the line EGA_ACCESS="/home/smith10/ega_access" and replace the filepath with a path for the file containing your own ega access credentials. See the details on setting an credentials file in the ega-download-client github repo documentation.

./scripts/download_cel.sh

Running Affytools

slurm-specific

sbatch sbatch_affy_run

or

./script/affy_SNP6_pipeline.sh

Running modified ASCAT pipeline

slurm-specific (implemented as a SLURM array)

sbatch sbatch_ascat_array_fixed_purity

This utilises the row number (after header) of the cellLine_CEL_file_mapping.tsv file to submit a number of array jobs. This submission works by sumbitting the array job index as a commandline variable to the ASCAT.sc script, where Rscript scripts/ASCAT.on.celllines_fixed_purity.R ${SLURM_ARRAY_TASK_ID} is run for each sample. The slurm job submission will need to be edited to match the number of rows (excluding header) in this file by editing the line #SBATCH --array=1-2230%200.

To run this section without slurm, please see the documentation on array jobs for your job management software to provide the correct index value to the Rscript scripts/ASCAT.on.celllines_fixed_purity.R ${SLURM_ARRAY_TASK_ID} or implement a parallelised looping script.

PBS

PBS-torque can be used by setting up a PBS job submission script matching the job requirements specified in the slurm job submission script and setting the array configuration line to #PBS -t 1-2230%200 and replacing the ${SLURM_ARRAY_TASK_ID} variable with ${PBS_ARRAYID}.

LSF

LSF can be used by setting up a LSF job submission script matching the job requirements specified in the slurm job submission script and setting the array configuration line to #BSUB -J arrayJob[1-2230:200] and replacing the ${SLURM_ARRAY_TASK_ID} variable with ${LSB_JOBINDEX}.

Local

The ASCAT.sc scatter-gather array can be run without a job management software. The slow solution is to implement the ASCAT.sc array job as a for loop;

for i in `seq 1 2230`; do
  Rscript scripts/ASCAT.on.celllines_fixed_purity.R $i;
done

A faster implementation, if xargs is available, is to run jobs in parallel though you should monitor resource usage carefully as this will start multiple R instances;

seq 1 2230 | xargs -n 1 -P 100 -I {} bash -c 'scripts/ASCAT.on.celllines_fixed_purity.R {}'

Where -P N is the number of concurrent jobs.

Quality control of cell line fits

Generate QC data

Rscript scripts/get_ploidy_purity.R
Rscript scripts/get_sc_ploidy_purity.R

or slurm-specific

sbatch sbatch_get_ploidy_purity
sbatch sbatch_get_sc_ploidy_purity

Generate unrounded copy number segments

Rscript scripts/generate_unrounded_sc_fixedPurity_tCN_file.R

Plot QC data

Rscript scripts/plot_summarised_segData.R

slurm-specific

sbatch sbatch_plot_summarised_segData

Perform fit selection and filtering

Inspect the copy number profile plots and statistics generated in the previous steps and update the cell_fit_qc_table.tsv file to include or exclude samples using a TRUE or FALSE boolean in the use column.

Re-generate unrounded copy number segments

Regenerate the unrounded segment file which now uses the cell_fit_qc_table.tsv to remove unwanted samples.

Rscript scripts/generate_unrounded_sc_fixedPurity_tCN_file.R

Generate copy number signatures

slurm-specific

sbatch sbatch_genPanCanSigs

or

Rscript scripts/quantify_signatures.R

The final output is a RDS object called cellLine_signature_data.rds which contains the CINSignatureQuantification object containing the signatures. A matrix of the threshold-corrected cell line by signature exposure is also written to the same directory.

Licence

The contents of this repository are copyright (c) 2022, University of Cambridge and Spanish National Cancer Research Centre (CNIO).

The contents of this repository are published and distributed under the GAP Available Source License v1.0 (ASL).

The contents of this repository are distributed in the hope that it will be useful for non-commercial academic research, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the ASL for more details.

The methods implemented in the code are the subject of pending patent application GB 2114203.9.

Any commercial use of this code is prohibited.