More figure analysis notebooks

data*

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notebooks/check_anndatas.ipynb

notebooks/reviewer_response_2.ipynb

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notebooks/_*.ipynb

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# progressive-plasticity-crc-metastasis

Notebooks for generating figures in "Progressive Plasticity During Colorectal Cancer Metastasis"

# Progressive Plasticity in Colorectal Cancer Metastasis

This repository accompanies the study *"Progressive Plasticity During Colorectal Cancer Metastasis"* published in *Nature* (available [here](https://www.nature.com/articles/s41586-024-08150-0)), aiming to reproduce key figures and analyses from the paper.

### Project Overview

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. 

### Repository Structure

- **data/**: Contains required data files:

  - **h5ads/**: AnnData files, such as `Tumor.h5ad`, `Epithelial.h5ad`, etc.

  - **tables/**: Supplementary tables in `.xlsx` format.

  - **other/**: Additional annotation and enrichment files.

- **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`).

### Data Access

The processed H5AD data for reproducing this analysis is hosted on AWS S3 at:

```

s3://dp-laba-data-public/progressive-plasticity-crc-metastasis

```

### Installation

To install the required dependencies, ensure you have Python 3.8 or higher and use the `pyproject.toml`:

```bash

pip install .

```

For specific package versions, review the `pyproject.toml`.

### Quickstart

1. **Download Data**: Start with `download_data.ipynb` to load data files from AWS.

2. **Run Notebooks**: Open notebooks in the `notebooks` directory to generate individual figures.

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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.