Whole genome doubling drives oncogenic loss of chromatin segregation

Ruxandra A. Lambuta, Luca Nanni, Yuanlong Liu, Juan Diaz-Miyar, Arvind Iyer, Daniele Tavernari, Natalya Katanayeva, Giovanni Ciriello and Elisa Oricchio

Running the analysis

You can run the whole set of analyses by simply running

bash run.sh

The script will:

1. Download the data necessary for the analysis from Zenodo
2. Run each analysis present in the src folder
3. Store the resulting figures in the figures folder

You can check the rest of this document to learn about each step of the pipeline.

00_download.sh

Downloads the data necessary for the analysis from the two Zenodo repositories:

• Part 1: https://doi.org/10.5281/zenodo.7351767
• Part 2: https://doi.org/10.5281/zenodo.7351776

It then merges the files in a single zip file, and finally decompress the archive into the data folder

01_hic_to_mcool.sh

Converts the *.hic files storing information about Hi-C experiments into *.mcool files for later processing.

02_LCS.py

It performs, for each sample comparison presented in the paper, the analyis of Loss of Chromatin Segregation (LCS). The analysis is done a three different levels:

• Inter-chromosomal interactions
• Inter-compartmental interactions
• Boundary insulation

03_ChIPSeq.py

It performs the analysis of ChIPSeq signals and peaks for CTCF and H3K9me3 between Control and WGD samples, as presented in the paper.

04_scHiC.py

Analysis of Single-cell Hi-C data, as presented in the paper. Specifically, the code will:

1. Analyse inter-chromosomal interactions in single cells
2. Perform pseudo-bulk inter-chromosomal analysis from single cells
3. Analyse compartment segregation at single cell level
4. Infer copy number changes for each single cell