amplicon_suite_ppcg

The original code and instructions are from https://github.com/AmpliconSuite/AmpliconSuite-pipeline . It has been modified to generate the seed intervals from the Battenberg calls, which are then passed to Amplicon Architect.

Installation

1. Download the list of samples, filter by country and remove the rows/samples that should not be included: /pptech_exchange/Working_Groups/Mutational_Processes/ecDNA/hlfa_list_all_countries.csv
   • Column 1: Sample name (Local ID)
   • Column 2: SCNA filename
   • Column 3: Country
2. Obtain the data repository containing the AmpliconSuite-pipeline image and GRCh37 annotations :
   • Download the data repo: /pptech_exchange/Working_Groups/Mutational_Processes/ecDNA/data_repo.tar.gz
   • Extract the tar file

     tar zxf data_repo.tar.gz

3. Obtain the execution script

   git clone https://github.com/uretaj/amplicon_suite_ppcg.git

4. License for Mosek optimization tool:

   • Obtain license file mosek.lic (https://www.mosek.com/products/academic-licenses/). The license is free for academic use.

   • Place the file in $HOME/mosek/ (i.e, the mosek/ folder that now exists in your home directory).

   • If you are not able to place the license in the default location, you can set a custom location by exporting the bash variable MOSEKLM_LICENSE_FILE=/custom/path/.

     export MOSEKLM_LICENSE_FILE="/path/to/mosek.lic"

An example command might look like:

amplicon_suite_ppcg/singularity/run_paa_singularity.py -o path/to/output_dir/sample --bam sample.bam --scna_file sample.txt --data_repo path/to/data_repo

Below is a sample Slurm file:

#!/bin/bash


#SBATCH --job-name=circdna.slurm
#SBATCH --ntasks=1
#SBATCH -t 48:00:00
#SBATCH --cpus-per-task=1
#SBATCH --mail-type=ALL
#SBATCH --output=%x.%a.%j.out # STDOUT 
#SBATCH --error=%x.%a.%j.err  # STDERR
#SBATCH --array=1-40
#SBATCH --mem-per-cpu=100G



module load singularity/3.8.2
export MOSEKLM_LICENSE_FILE="mosek/mosek.lic"
echo "ARRAY ID: ${SLURM_ARRAY_TASK_ID}"
filename=$(head -n ${SLURM_ARRAY_TASK_ID} hlfa_list_all_countries.csv  | tail -1)
filename=${filename%$'\r'}
IFS=',' read -ra arr <<< "$filename"
sample=${arr[0]}
cnv=${arr[1]}
echo "SAMPLE ${sample}"
echo "FILENAME ${cnv}"
pathf="BAM/${sample}.mapped.bam"
cnvpath="Subclonal_SCNA_with_Avg_CN/${cnv}
amplicon_suite_ppcg/singularity/run_paa_singularity.py  -o AA_RESULT/${sample} -t 1 --bam ${pathf}  --scna_file ${cnvpath} --data_repo path/data_repo

Here's an example of how to submit a job arrray to run multiple samples (i.e. execute the script for 40 samples but only run 5 samples at a time)

sbatch --array=1-40%5 amplicon_suite.slurm

Command line arguments to AmpliconSuite-pipeline

Required

• -o {outdir}: Directory where results will be stored. Include the sample name to avoid conflicts.
• --data_repo {repodir} : Directory where the singularity image file and required annotations for GRCh37 are stored.
• -t : Number of threads but it's not really used so just set it to 1.

Input files:

• --bam {sample.bam} Coordinate-sorted bam
• --scna_file {scna.txt} Supply the Battenberg SCNA calls of the sample to generate the seed intervals to be passed to Amplicon Architect. Please use the May 2023 SCNA calls from: /data_releases/WGS_Data_Release/Somatic_variants/SCNA/SCNA_with_BD_SVs_03_05_2023.tar.gz.gpg