This repository accompanies the study "Progressive Plasticity During Colorectal Cancer Metastasis" published in Nature (available here), aiming to reproduce key figures and analyses from the paper.
The study investigates the progressive plasticity of cellular states during the metastasis of colorectal cancer. Using single-cell RNA sequencing data from primary tumors and metastases, we uncover dynamic cellular state transitions, highlighting specific lineage and state shifts associated with metastatic progression.
data/: Contains required data files:
Tumor.h5ad
, Epithelial.h5ad
, etc..xlsx
format.notebooks/: Jupyter notebooks for data download, preprocessing, and reproducing figures:
download_data.ipynb
: Guide for downloading data directly from AWS S3.Figure_X.ipynb
: Notebooks for reproducing figures in the paper.src/: Source code modules organized by functionality, including utilities for data preprocessing (pp
), plotting (pl
), and label transfer or state analysis (tl
).
The processed H5AD data for reproducing this analysis is hosted on AWS S3 at:
s3://dp-lab-data-public/progressive-plasticity-crc-metastasis
You can download directly using the following links:
https://dp-lab-data-public.s3.us-east-1.amazonaws.com/progressive-plasticity-crc-metastasis/h5ads/All.h5ad
https://dp-lab-data-public.s3.us-east-1.amazonaws.com/progressive-plasticity-crc-metastasis/h5ads/Epithelial.h5ad
https://dp-lab-data-public.s3.us-east-1.amazonaws.com/progressive-plasticity-crc-metastasis/h5ads/KG146_Organoids.h5ad
https://dp-lab-data-public.s3.us-east-1.amazonaws.com/progressive-plasticity-crc-metastasis/h5ads/KG146_Tumor.h5ad
https://dp-lab-data-public.s3.us-east-1.amazonaws.com/progressive-plasticity-crc-metastasis/h5ads/KG146_Tumor_Mapping_Reference.h5ad
https://dp-lab-data-public.s3.us-east-1.amazonaws.com/progressive-plasticity-crc-metastasis/h5ads/KG146_shPROX1_Knockdown.h5ad
https://dp-lab-data-public.s3.us-east-1.amazonaws.com/progressive-plasticity-crc-metastasis/h5ads/KG150_Tumor.h5ad
https://dp-lab-data-public.s3.us-east-1.amazonaws.com/progressive-plasticity-crc-metastasis/h5ads/KG182_Tumor.h5ad
https://dp-lab-data-public.s3.us-east-1.amazonaws.com/progressive-plasticity-crc-metastasis/h5ads/KG183_Tumor.h5ad
https://dp-lab-data-public.s3.us-east-1.amazonaws.com/progressive-plasticity-crc-metastasis/h5ads/Non-Tumor_Epithelial.h5ad
https://dp-lab-data-public.s3.us-east-1.amazonaws.com/progressive-plasticity-crc-metastasis/h5ads/Tumor.h5ad
https://dp-lab-data-public.s3.us-east-1.amazonaws.com/progressive-plasticity-crc-metastasis/h5ads/Untreated_Epithelial.h5ad
https://dp-lab-data-public.s3.us-east-1.amazonaws.com/progressive-plasticity-crc-metastasis/h5ads/Wang_etal_Tumor.h5ad
https://dp-lab-data-public.s3.us-east-1.amazonaws.com/progressive-plasticity-crc-metastasis/h5ads/Wang_etal_s1231_Tumor.h5ad
To install the required dependencies, ensure you have Python 3.8 or higher and use the pyproject.toml
:
pip install .
For specific package versions, review the pyproject.toml
.
download_data.ipynb
to load data files from AWS.notebooks
directory to generate individual figures.This README provides a basic overview of the repository's contents and is designed to support the reproducibility of key analyses and findings from the paper.