CNSistent 0.7.3

Tools for imputation, segmentation, analysis, and plotting of Copy Number Segments (CNS).

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.

READ THE DOCS HERE

CNSistent can be used as a Python package, or downloaded together with the respective data (PCAWG, TRACERx, TCGA, genomic locations):

Installation links

1. Full Bitbucket repository with ~1GB of data.
2. PIP package only.

Data

The input dataset is also availble on Zenodo: .

The processed is availble on Zenodo: .

Deep learning code is available on Zenodo: .

Acessions

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

MIT License