This is a public repository containing scripts described in the publication:
Lysenkova Wiklander et al. "A multiomic characterization of the leukemia cell line REH using short- and long-read sequencing" https://doi.org/10.26508/lsa.202302481
Sequencing data and BAM files for this project are available at NCBI/SRA under the BioProject accession numbers PRJNA600820 and PRJNA834955. These data have been analyzed on a high performance cluster (HPC) using the commands in 01_hpc_processing. The resulting analysis datasets are available at https://doi.org/10.5281/zenodo.108757278.
The scripts are numbered in the order they should be executed.
For HPC scripts, the full paths to source files have been omitted for simplicity. You will need to adjust them to your environment.
To run the other scripts in this repository, you will need to do the following.
Install:
- R 4.2.1 and an integrated environment, e.g. RStudio
- R packages: chromoMap, RColorBrewer, VennDiagram
- Python 3.8
- Necessary Python packages:
pip install -r requirements.txt - SURVIVOR v1.0.7 built from: https://github.com/fritzsedlazeck/SURVIVOR and placed in the directory
02_sv_callset_analysis/bin
Download the files from Zenodo and place them in the following directories:
data/coverage:
- copycat.ont.coverage.10kb.csv
- copycat.pb.coverage.10kb.csv
- copycat.pcrfree.coverage.10kb.csv
data/sv_callsets:
- illumina.tiddit.vcf
- ont.sniffles.vcf
- pb.sniffles.vcf
data/fusion_callsets/long_read:
- cupcake.long.csv
- cupcake.std.csv
- jaffa_results.csv
data/fusion_callsets/short_read:
- GM12878.fusionreport.txt
- illumina.all.txt
- illumina.filtered.csv
- REH.arriba.fusions.tsv
- REH.fusioncatcher.fusion-genes.txt
- REH.pizzly.txt
- REH.squid.fusions.annotated.txt
- REH.starfusion.abridged.tsv