dsh-ezprot-plugin

Proteomics data analysis has always sat behind a steep learning curve. Normalization, batch correction, differential testing, pathway enrichment — each step demands R scripts and terminal fluency that keeps many wet-lab biologists locked out of their own results. dsh-ezprot-plugin collapses the entire pipeline into a single conversation: tell the agent where your data file lives, what the sample groups are, and which comparisons you need, and it drives every stage from QC all the way to a final interpretation report without you writing a line of code.

The workflow spans the full expression-analysis chain: data QC and normalization, PCA visualization, batch-effect correction, differential protein analysis, GO/KEGG functional enrichment, and GSEA gene-set enrichment. Every stage produces a readable summary with figures, and the session closes with an interpretation report highlighting top differential proteins, enriched pathways, and candidate targets — visible, traceable, and reproducible.

On first use the plugin detects and silently installs an R 4.4.0 runtime with its package library (roughly 10–20 minutes, one-time). When a local R setup is not feasible it falls back to a Docker backend automatically, and can still complete the one-time GO/KEGG background build on network-restricted machines. There is no manual configuration to manage.

If you have a proteomics raw-data export and a sample-info sheet but do not want to spend weeks learning R, DESeq2, or limma, this plugin is built for you: open a chat, describe your groups, and let the agent handle the rest.