https://github.com/borgwardtlab/human_scdvp_analysis
https://github.com/borgwardtlab/human_scdvp_analysis
Last synced: 11 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/borgwardtlab/human_scdvp_analysis
- Owner: BorgwardtLab
- License: bsd-3-clause
- Created: 2025-02-24T13:08:57.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-26T14:32:19.000Z (about 1 year ago)
- Last Synced: 2025-03-26T14:43:12.900Z (about 1 year ago)
- Language: Python
- Size: 31.5 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Human scDVP data analysis
Data analysis scripts for "Spatial single-cell proteomics enables continuous mapping of protein gradients in human liver tissues".
### Installation
To install the software, first create an isolated conda environment, and add [poetry](https://python-poetry.org/) (our dependency manager of choice) to its dependencies:
```bash
conda create -n humanscDVP python=3.11 poetry
conda activate humanscDVP
```
Navigate to the repository folder, and run:
```bash
poetry install
```
In order to convert mouse gene names to their human orthologs, you will also need to install the [pyorthomap](https://github.com/vitkl/orthologsBioMART) package from GitHub:
```bash
pip install git+https://github.com/vitkl/orthologsBioMART.git
```
### Usage
To reproduce the output provided in `results`, run the following sequence of commands:
1. Run LMM analysis for control human samples:
```bash
python LMM_analysis.py --data_path ../data/human/ --patient_group 1 --plot --save --species human
```
2. Run LMM analysis for fibrotic human samples:
```bash
python LMM_analysis.py --data_path ../data/human/ --patient_group 2 --plot --save --species human
```
3. Run LMM analysis for mouse samples:
```bash
python LMM_analysis.py --data_path ../data/mouse/ --patient_group 3 --plot --save --species mouse
```
4. Compare slopes between control and fibrotic human samples:
```bash
python Compare_slopes.py --control_model_results ../results/human_controls/results_1_cutoff\=0.7.tsv --treatment_model_results ../results/human_fibrotic/results_2_cutoff\=0.7.tsv --plot --one_sided
```