This tool was created for use by Deepika Awasthi's team at JBEI laboratories to automate proteomic analysis. It is a simple script that provides fold change values and p-values in an Excel sheet, and volcano plot figures.

1. Clone this repo

   • If you have git installed, run git clone [email protected]:adkala/portfolio.git
   • Else, click the green 'Code' button on this page and click 'Download ZIP'
     • Unzip file before continuing

2. Install python3 if you don't have it

   • Can be downloaded from here https://www.python.org/downloads/

3. Install necessary packages

   • From terminal, navigate to this directory (use cd ~/Downloads/proteomics_analysis if in downloads)
   • Run pip install -r requirements.txt
     • if pip doesnt work, try pip3

4. Create 'edited' tab on Excel file according to these specifications:

   • 'Identified Proteins' column at column 1
   • 'Alternate ID' column at column 2
   • Protein values in columns 3 and beyond
   • Example Photo:

5. Place Excel files in proteomics_analysis folder

   • This can be changed in the .env file with the START_PATH variable

6. Use Python notebook prot.ipynb to run blocks and create figures and Excel files with analyzed data

   • Legacy option is using the prot.py script
     • To use:
       • From terminal, in proteomics_analysis folder, run python3 prot.py *excel files* *denominator* *numerators*
         • For example, to compare 'GLU' and 'HBA' against 'PCA' in KT2440_A.xlsx and KT2440_B.xlsx, run python3 prot.py KT2440_A.xlsx,KT2440_B.xlsx PCA GLU,HBA
       • To edit variables such as start path, end path, and quantitative threshold, edit the .env file.
         • If you can't see the .env file, enable hidden files in your file explorer.

Feel free to contact me at [email protected]. Would be happy to discuss!