https://github.com/cnpem/ddx3x-stress-granules-analyses

https://github.com/cnpem/ddx3x-stress-granules-analyses

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• Host: GitHub
• URL: https://github.com/cnpem/ddx3x-stress-granules-analyses
• Owner: cnpem
• Created: 2024-11-19T13:47:18.000Z (2 months ago)
• Default Branch: main
• Last Pushed: 2024-12-02T17:36:05.000Z (about 2 months ago)
• Last Synced: 2024-12-02T18:45:51.167Z (about 2 months ago)
• Language: TeX
• Homepage: https://cnpem.github.io/ddx3x-stress-granules-analyses/
• Size: 72.5 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# DDX3X Stress Granules Analysis

This repository contains the analysis pipeline for investigating stress granules in DDX3X variants using microscopy data. The analysis includes cell segmentation, stress granule detection, and statistical analysis of granule properties.

## Prerequisites

1. Install [uv](https://github.com/astral-sh/uv) for Python package management

2. Install [Quarto](https://quarto.org/docs/get-started/) for report generation

## Setup

1. Clone this repository:

```bash

git clone https://github.com/username/ddx3x-stress-granules-analyses.git

cd ddx3x-stress-granules-analyses

```

2. Use `uv sync` to create a virtual environment and install depedencies:

```bash

uv sync

```

3. Activate the virtual environment:

```bash

source .venv/bin/activate

```

## Data

The microscopy data is not included in this repository due to size constraints but is available on Zenodo [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.14224482.svg)](https://doi.org/10.5281/zenodo.14224482).

## Running the Analysis

Generate the analysis report using Quarto:

```bash

quarto render . --output-dir report

```

This will create a `report` directory containing the complete analysis. Open `report/index.html` in your web browser to view the results.

## Directory Structure

- `data/`: Raw microscopy images (not included in repository)

- `figures/`: Generated images showing three processing stages for each analyzed image:

  1. Maximum intensity projection

  2. Filtered channel

  3. Cell and granule detection results

- `output/`: CSV files containing:

  - `granule_area.csv`: Measurements of individual stress granules

  - `granules_per_cell.csv`: Cell-level granule counts and metrics

- `plots/`: Generated plots and visualizations including:

  - Violin plots comparing granule areas across conditions

  - Violin plots showing granule count distributions

  - Bar plots of cell percentages with different granule counts

- `report/`: Generated analysis report (after running Quarto)