The project involves computational analysis and interpretation of processed chromatin conformation capture data (Hi-C). The data has been generated from tumor samples obtained from patient-derived xenograft (PDX) models. The experimental conditions include two triple-negative breast cancer PDX cells grown as primary tumors and drug-resistant clones.
Main goal is to identify changes in the 3D genome organization between drug-resistant (CR) and primary (Primary) tumors. Analyses include comparison of 1) Distance-dependent decay of interaction frequencies; 2) A/B compartments; 3) Topologically Associating Domains; 4) Chromatin loops. The outcome includes visualization and genomic coordinates of altered regions (changes in chromatin interactions).
Supplementary data include differential gene expression, CNVs, SNPs, InDels, SVs.
- Create HiC files using Juicer, see 01_create_hic_files for more details.
- Exploratory analysis of biological replicates, specifically MDS, PCA, and distance decay (contact probability) plots. See 02_visualize_replicates for more details.
- If appropriate (based on #2), merge biological replicates to increase resolution. See 03_merge_replicates for more details.
- Same as #2, but using output from #3. See 04_post_merge_analysis for more details.
- Use HiC Explorer and custom python script to visualize and quantify differences in TAD attributes between samples. See 05_differential_tads for more details.
- Use Homer to quantify AB compartment switches between samples. See 06_ab_compartments
- Use NeoLoopFinder to discover structural variants between samples. See 07_structural_variants for more details.