This is for EuchroGene Members.

PyDESeq2 is a Python-based Differentially Expressed Gene analysis tool.

Two inputs are required.

1. A CSV file for experiment design.

2. A CSV file for gene expression counts.

A CSV (Comma-separated value) file can be generated in Microsoft Excel by saving the file as CSV (Comma-delimited) (*.csv).

You can use the gene expression counts generated from the RNA-seq_to_TPM_STAR or RNA-seq_to_TPM_Bowtie2 in this repository.

You can refer to the format of the experiment design file in this repository.

Outputs are DEGs, Volcano plot, MA plot, and PCA plot of samples.

To install, copy and paste the following commands in a Jupyter Terminal, and execute:

0. Install EG_tools (*** If this is already installed, skip this step ***)

wget https://github.com/euchrogene/EG_tools/raw/refs/heads/main/EG_tools
sudo chmod 777 EG_tools
sudo mv EG_tools /usr/bin

1. install the software:

sudo EG_tools install -r https://github.com/euchrogene/PyDESeq2.git -d PyDESeq2 -e PyDESeq2_v.1.0 -m "Analyze Differentially Expressed Genes (DEGs) using PyDESeq2."

2. display installed software

EG_tools

3. download example files (use the same format for your data)

wget https://github.com/euchrogene/PyDESeq2/raw/refs/heads/main/Example_Exp_design.csv  # This will download the experiment format file
wget https://github.com/euchrogene/PyDESeq2/raw/refs/heads/main/Example_Gene_Exp_Count.csv # this will download the gene expression count file

4. example run

PyDESeq2_v.1.0 -exp_design_csv Example_Exp_design.csv -count_table Example_Gene_Exp_Count.csv -exp_name test

5. show help contents

PyDESeq2_v.1.0

Help contents:

________________________________________________________________________________________________

Used Tool: pydeseq2 (a python package) - Production Level

This is a software for DESeq2 analysis. It uses the PyDESeq2 Python package.
The results include DEGs, a Volcano plot, an MA plot, and a PCA plot of samples.

If you find any bugs, please email: bioinformatics@euchrogene.com
________________________________________________________________________________________________

Usage:

-help                show options
-exp_design_csv      (required) csv file name for experimental design
-count_table         (required) csv file name for gene expression count table
-exp_name            (option) name of experiment (default: 'Sample')
-log2fc              (option) threshold for log2fc (default: 1.0) 
-padj                (option) threshold for adjusted p-value (default: 0.05) 

Example:
    PyDESeq2 -exp_design_csv design.csv -count_table counts.csv \\
             -exp_name stress_response -log2fc 1.5 -padj 0.01
______________________________________________________________________________________________

6. Uninstall old version

sudo EG_tools uninstall -t PyDESeq2 -i managene7/rna-seq_to_tpm_deseq2:v.1.0

6. Uninstall v.1.0

sudo EG_tools uninstall -t PyDESeq2_v.1.0 -i managene7/rna-seq_to_tpm_deseq2:v.1.1

Citation

PyDESeq2

Boris Muzellec, Maria Teleńczuk, Vincent Cabeli, Mathieu Andreux, PyDESeq2: a python package for bulk RNA-seq differential expression analysis, Bioinformatics, Volume 39, Issue 9, September 2023, btad547, https://doi.org/10.1093/bioinformatics/btad547