ProHits-viz
ProHits-viz is a browser-based visualization and analysis suite for scored, quantitative protein–protein interaction datasets generated by affinity purification–mass spectrometry (AP–MS). It is designed to complement existing interaction-scoring pipelines by providing standardized, publication-ready visual summaries that more directly communicate prey abundance and confidence across multiple bait purifications than conventional node–link network views. ProHits-viz supports direct import from widely used workflows, including SAINT and the CRAPome, and also accepts generic tabular inputs with automated detection of bait, prey, abundance, and score fields and configurable parameter defaults.
The suite comprises four main analytical modules with integrated figure generation: (1) bait–prey clustering to produce dot plots that encode raw abundance, relative abundance across baits, and interaction confidence; (2) bait and prey correlation analysis rendered as clustered heat maps, including prey-centric correlation to reveal shared interaction profiles suggestive of co-complex membership or co-localization; (3) prey specificity scoring for each bait–prey pair (including fold enrichment and CompPASS-derived metrics) to identify preferential associations; and (4) detailed bait–bait comparisons that summarize significant preys in compact scatter plots. Outputs can be viewed interactively in the browser—supporting zooming, fisheye label enlargement, reordering or filtering of rows/columns, region-of-interest selection, and downstream annotation/analysis—and exported as vector graphics (SVG) or downloaded as PDF figure packages for publication and reporting.
Topics
Details
- Maturity:
- Mature
- Cost:
- Free of charge
- Tool Type:
- web application, workflow
- Operating Systems:
- Linux, Windows, Mac
- Added:
- 6/4/2018
- Last Updated:
- 11/25/2024
Operations
Publications
Knight JDR, Choi H, Gupta GD, Pelletier L, Raught B, Nesvizhskii AI, Gingras A. ProHits-viz: a suite of web tools for visualizing interaction proteomics data. Nature Methods. 2017;14(7):645-646. doi:10.1038/nmeth.4330. PMID:28661499. PMCID:PMC5831326.