This tool now includes ruptures changepoint detection using BinSeg and kernelCPD algorithms, for estimation of CNV breakpoints. More details on how these algorithms work can be found here. Happy plotting.
The centromeric/acroscentric regions are identified using the t2t-chm13-v1.0 database for GRCh38 found here.
To initiate a python environment:
python -m venv cnv_env
Install package requirements:
pip install -r requirements.txt
Activate environment:
source cnv_venv/bin/activate
Usage: cnv_gene_plot_ruptures.py [OPTIONS] path/to/BAM
Options:
-c, --chromosome TEXT Chromosome to plot.
-g, --gene_panel_path path/to/bed.bed Gene bed file to choose
-s, --sub_gene_path path/to/genes.txt Use file to select genes to display
-x, --x_coords INTEGER-INTEGER Hyphen-separated base coordinates to plot for
the selected chromosome
-o, --output_file TEXT.pdf Select output PDF file
-r, --ruptures Include ruptures changepoint detection
-m, --method [BinSeg|kernelCPD] Changepoint detection method to use
-f, --file_list PATH Path to a .txt file containing a list of BAM
file paths
--help Show this message and exit.
# Generates a CNV plot of chromosome 1 from position 10000000 to 20000000
python3 cnv_gene_plot.py /home/bam_files/test.bam -c chr4 -x 10000000-20000000
# Generates plot of chromosome 1 with all genes from the rCNS panel labelled accordingly
python3 cnv_gene_plot.py /home/thomas/sort_ds1305_Intraop0002_2.htom.bam -c chr4 -g rCNS2_panel_name_uniq.bed
# Generates a plot of chromosome 1 with selected genes found in select_genes.txt from the rCNS2 panel with ruptures kernel changepoint detection
python3 cnv_gene_plot.py /home/thomas/sort_ds1305_Intraop0002_2.htom.bam -c chr1 -g rCNS2_panel_name_uniq.bed -s select_genes.txt -r -m kernelCPD