Skip to content

arnikz/PIQMIe

Folders and files

NameName
Last commit message
Last commit date

Latest commit

33d7b5d · Sep 12, 2024

History

91 Commits
Sep 12, 2024
Dec 30, 2017
Oct 17, 2020
Dec 20, 2017
Sep 10, 2024
Aug 14, 2019
Sep 12, 2024
Sep 27, 2015
Apr 26, 2020
Apr 26, 2020
Sep 12, 2024
Sep 10, 2024
Sep 12, 2024
Sep 10, 2024
Sep 10, 2024
Sep 10, 2024
Aug 14, 2019
Sep 4, 2024
Sep 12, 2024
Sep 5, 2024

Repository files navigation

PIQMIe

DOI Published in NAR CI

Description

PIQMIe is a web-based tool for reliable analysis and visualization of semi-quantitative mass spectrometry (MS)-based proteomics data. PIQMIe readily integrates peptide and (non-redundant) protein identifications and quantitations, as obtained by the MaxQuant/Andromeda software (Cox et al., 2008, 2011), with additional biological information from the UniProtKB database, and makes the linked data available in the form of a light-weight relational database (SQLite). Using the web interface, users are presented with a concise summary of their proteomics experiments in numerical and graphical forms, as well as with a searchable protein grid and interactive visualization tools to aid in the rapid assessment of the experiments and in the identification of proteins of interest. PIQMIe provides data access via a web interface and programmatic RESTful API.

Prerequisites

Software stack

  • perl
  • python
    • cherrypy
    • genshi
    • cairo
  • sqlite
  • javascript/css
    • jquery
    • d3.js
    • bootstrap

Install

1. Clone this repository.

git clone https://github.com/arnikz/PIQMIe.git

2. Build and deploy web app.

cd PIQMIe
docker build -t piqmie .
docker run -d -p 8080:8080 piqmie

Usage

To view the sample data on your local PIQMIe instance, follow Sample Data tab and click on results.

Alternatively, upload your own data files, i.e., MaxQuant peptide (evidence.txt) and protein (proteinGroups.txt) lists including the sequence library in FASTA (.fa|fasta), to the web server and click on the Submit button to process the input files. After processing, click on the generated link to view the results. Note: For each session, a new (sub)directory <DATA_DIR>/<jobID> including I/O files will be created.