scRNA-seq data analysis 🧫

Alberti A., Ianniciello S., Magos P.M., Testa I., Tolloso M.

This repository contains the scripts used to perform the data analysis presented in the report “Comparison between COTAN and state of the art libraries for the analysis of scRNA-seq data” for the “Computational Health Laboratory” course at the University of Pisa (a.y. 2022/2023).

How to run

We assume you are working on unix-like systems (Linux, MacOS, Windows Subsystem for Linux).

Colone the repository

git clone https://github.com/arcotan/single-cell-data-analysis.git

Move to the repository folder

cd single-cell-data-analysis

Download the datasets with the following command:

wget "https://unipiit-my.sharepoint.com/:u:/g/personal/m_tolloso_studenti_unipi_it/ESX8nFEDsHdMo5_mBAiAgBIB6aDBPwyVSNqgqnDsB2__RQ?e=LhIna1&download=1" -O dataset.zip &&
wget "https://unipiit-my.sharepoint.com/:u:/g/personal/m_tolloso_studenti_unipi_it/ERFzNbWhOq1EkDz5ntlopOIB0VZ8kxKBssaYZTxwVmPqMA?e=mU5RE6&download=1" -O filtered.zip &&
wget "https://unipiit-my.sharepoint.com/:u:/g/personal/m_tolloso_studenti_unipi_it/ERBF-kbdUCpHn1O1wWCpaT4ByoSsAuxdLbvOcBHUcf1buw?e=Xgiy8T&download=1" -O results.zip && 
unzip dataset.zip &&
unzip filtered.zip &&
unzip results.zip &&
rm dataset.zip &&
rm filtered.zip &&
rm results.zip

(All the results are precomputed)

You can still run all the analysis code, executing the following command:

chmod +x run.sh &&
./run.sh