pquant

pquantR is a python and R package to perform downstream analysis of proteomicsLFQ quantitative data. It also included R shiny application which is designed to do the downstream analysis of proteomics dataset, currently these figures are included: Heatmap, Volcano Plot, QC plot.

Because the application is in developing, the test figures are drawn by test R packages separately now.

Installation of environment

The build.sh bash script use conda and mamba to install the environment to install all the dependencies and packahes in python and R.

Prerequisites:

• conda (https://conda.io/projects/conda/en/latest/user-guide/install/index.html)
• mamba (https://github.com/mamba-org/mamba)

After the installation of conda and mamba you can run the following script:

$> source build.sh

sample datasets

• UPS1:
  • Configuration run from proteomicsLFQ (unique peptides, star align, stricter pep and protein FDR) - unique-peptides-star-align-stricter-pep-protein-FDR
  • Configuration run from proteomicsLFQ (unique peptides, target-only, star align, stricter pep and protein FDR) - unique-peptides-target-only-star-align-stricter-pep-protein-FDR

Shiny application

1. Preparing for shiny app.
   

• Download pquantR folder from this page and put it in a suitable working path.

2. Run app.R in the folder, and you could run it in the following ways.
   

• Upload the data, choose the parameters of MSstats then submit.
  

3. We could see visualization of processed data and differentially abundant proteins.
   

Todo list

1. Add download function, including PDF,PNG format, etc.
   
2. Other interactive plots.