CNSistent is a Python tool for processing and analyzing copy number data. It is designed to work with data from a variety of sources. The tool is designed to be easy to use, and to provide a comprehensive set of analyses and visualizations.
CNSistent can be used as a Python package, or downloaded together with the respective data (PCAWG, TRACERx, TCGA, genomic locations):
The input dataset is also availble on Zenodo: 
The processed is availble on Zenodo: 
Deep learning code is available on Zenodo: 
The contents of the data folder were obtained by processing the following sources, accessed in December 2023.
TCGA data obtained from ASCATv3 at: https://github.com/VanLoo-lab/ascat/tree/master/ReleasedData
Cite: https://www.pnas.org/doi/full/10.1073/pnas.1009843107
The results published here are in part based upon data generated by the TCGA Research Network: https://www.cancer.gov/tcga.
PCAWG data obtained from: https://dcc.icgc.org/releases/PCAWG/consensus_cnv Cite: https://www.nature.com/articles/s41587-019-0055-9
TRACERx data obtained from: https://zenodo.org/records/7649257
Cite: https://www.nature.com/articles/s41586-023-05729-x
COSMIC cancer set obtained from: https://cancer.sanger.ac.uk/census
Cite: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6450507
Human genome gene set obtained using PyENSEMBL (2023). Cite: https://academic.oup.com/nar/article/51/D1/D933/6786199
Cytoband, Gap data obtained from: https://genome.ucsc.edu Cite: https://www.nature.com/articles/35057062
Cite Adam Streck, Roland F Schwarz, CNSistent integration and feature extraction from somatic copy number profiles, GigaScience, Volume 14, 2025, giaf104.
The code is available under the MIT License.
The data and text files in the data and docs folders are available under the CC BY-NC 4.0 license.