Discover drug candidates from gene signatures

Sig2Drug allows to analyze differential gene expression data and find compounds that reverse disease signatures.

Data analysis Publication

Signatures

Compounds

Cell-based models

DISEASE VS CONTROL

→

Sig2Drug

reversing signatures

Drug A

vs control

Drug B

vs control

Drug C

vs control

Data Analysis

Upload disease vs control signatures with gene symbols and statistics

Analysis Method

ℹ️ Note: Up/down lists → XSum or KS only. With statistics or count matrix → all methods.

✓ Accepted: t-stat, z-score, Wald stat, signed -log10(p/FDR) | ⚠ logFC alone (noisy)

Human genes only: Either gene symbols (e.g. TP53, BRCA1) and/or Ensembl IDs (e.g. ENSG00000141510). Non-human? Map to human orthologs first.

Example Datasets

| .xlsx .xlsx .xlsx

Up/Down Lists Ranked List Count Matrix

Upregulated Genes

Downregulated Genes

For KS and XSum methods only

Gene Symbols with Statistics

Drop file here or browse

.xlsx, .csv, .txt, .tsv

Or paste data

Format: gene,statistic (tab/comma/semicolon). Order from most upregulated to most downregulated.

Count Matrix (Tab-separated)

Drop file here or browse

.xlsx, .csv, .txt, .tsv

Example: UC vs Control (GSE16879)

Or paste data

Format: First column = gene symbols. Column names must contain disease or control (case-insensitive).
Example: gene, UC_1, UC_2, Control_1, Control_2 → UC samples vs Control samples