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Subnetwork analysis on proteomics data

Background: I have proteomics data from seven samples (pvalue/ log-score of fold change), I want to analyze the data by network (interactome) analyses.

Question: I like to create an interactome of all the proteins from the data, and map the proteins to this network that have significant pvalue (compare to control), after that I like to create subnetwork(s); also like to add the pathways enrichments to the subnetwork(s).

Request: please suggest online or standalone tools (or algorithm) that fits my requirements.

Thanks !

proteomics data python
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updated by Khader Shameer Khader Shameer • written by ahmedakhokhar ahmedakhokhar

1 answer

We have done something similar to do what you are looking for to identify essential proteins for downstream analyses of human proteome-nanoparticle interactions, and it's biological significance.

  • Proteomics: MS-MS > Protein List > FDR filtering
  • Canonical or contextual networks: Proteins to Networks using STRING/GeneMania > Full or pruned network
  • Network analyses: Cytoscape for network analyses and visualisation > NetworkAnalyzer > Network parameters. Another option is to run module detection algorithms to detect cliques or graphlets in your network using GraphletCounter, MCODE etc.
  • Biological inferences: Use the node-based scores or module-set/subnetworks/cliques to run enrichment analyses for biological inferences

Manuscript on protein-nanoparticle proteomics + network analyses paper here: Understanding protein-nanoparticle interaction: a new gateway to disease therapeutics.

Manuscript discussing application of graphlet/clique analyses using plant stress network here: Network Modules Driving Plant Stress Response, Tolerance and Adaptation: A case study using Abscisic acid Induced Protein-protein Interactome of Arabidopsis thaliana

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written by Khader Shameer Khader Shameer

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