PIQMIe is a web-based tool for reliable analysis and visualization of semi-quantitative mass spectrometry (MS)-based proteomics data (Kuzniar and Kanaar, 2014). 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.
Python modules:
- cherrypy (>=3.2.2)
- genshi (>=0.7)
- sqlite3 (>=2.6.0)
- cairosvg (>=1.0.6)
- magic (>=0.4.3)
Javascript libraries:
- jQuery (>=1.11.0)
- jqGrid (>=4.6.0)
- D3.js (>=3.3.6)
git clone https://github.com/arnikz/PIQMIe.git
cd PIQMIe
virtualenv .venv
source .venv/bin/activate
pip install -r requirements.txt
Extract sample data on human bone development and mineralization (Alves et al., 2013).
cd data
tar xvf sampledata.tar.bz2
Edit config.ini file depending on dev or prod mode.
#environment = "production"
server.socket_host = "127.0.0.1" # in prod: 0.0.0.0
server.socket_port = 8080 # in prod: 80
...
tools.staticdir.root = "<APP_BASE_DIR>"
tools.staticdir.dir = "PIQMIe"
tools.sessions.storage_path = "<DATA_DIR>" # default: PIQMIe/data
...
log.error_file = "error.log" # in prod: /var/log/piqmie/error.log
log.access_file = "access.log" # in prod: /var/log/piqmie/access.log
Start up the web server.
cd <APP_BASE_DIR>
cherryd -i PIQMIe -c PIQMIe/config.ini # in prod: sudo ...
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.
Kuzniar, A. and Kanaar, R. (2014) PIQMIe: a web server for semi-quantitative proteomics data management and analysis, Nucleic Acids Research, 42, W100–W106. doi:10.1093/nar/gku478
Kuzniar, A. PIQMIe version 1.0. doi:10.5281/zenodo.34090