This repository includes the codes for the manuscript: 'Single cell genome and epigenome co-profiling reveals hardwiring and plasticity in breast cancer'.
It includes: 1) codes for processing and analyzing wellDA-seq data, and 2) codes for repeating the analysis and figures in the manuscript. Specifically, this repository is organized as following folders:
| Folder | Purpose | Visibility |
|---|---|---|
| install | Installing the required the command line tools and packages of R and Python languages. | public |
| tutorial | This tutorial uses a real sample in the manuscript to demonstrate how to preprocess and analyze wellDA-seq data. It introduces all the preprocessing steps, routine and advanced analysis that we applied to each of the samples in the manuscript. | public |
| preprocessing | Scripts to take the BCL files of wellDA-seq to create the single-cell CNA and ATAC matrices files. This is for the generic wellDA-seq users to pre-process the wellDA-seq data. | public |
| analysis | Codes of computational analysis used in the manuscript. This folder is organized in the order of applications. | private |
| figure | Codes of data visualization shown in the manuscript. This folder is organized in the order of figures. | private |
| data_portal | Data objects of input and output. | private |