TRACE: Data for Cross-Disease Transcriptomic Drug Repurposing

Published: 8 July 2026| Version 1 | DOI: 10.17632/fy93xjjrb8.1
Contributor:
Nisarg Oza

Description

This dataset contains all processed and derived data supporting the manuscript "TRACE: An Externally Validated Cross-Disease Framework for Transcriptomic Drug Repurposing" (Oza, N.). TRACE (Transcriptomic Reversal And Convergent Evidence) is a computational drug-repurposing framework that scores 1,768 LINCS L1000 small-molecule compounds by their capacity to reverse disease-associated gene expression signatures, benchmarked across three independent diseases spanning fibrotic and autoimmune/inflammatory pathophysiology: idiopathic pulmonary fibrosis (IPF), rheumatoid arthritis (RA), and ulcerative colitis (UC). The dataset is organized into eleven folders: differential_expression (per-cohort differential expression results for all 10 GEO cohorts used across the three diseases), disease_signatures (meta-analysis consensus signatures for IPF, RA, and UC), drug_scores (reversal and network-propagated scores for all 1,768 drugs across all three diseases), known_actives (curated positive and negative control compound lists per disease), crispr (genome-wide CRISPR knockout reversal screen results), l2s2 (expanded 2,834-compound drug-universe reversal scores), scrna (single-cell AT2→AT1 alveolar epithelial transition signature and associated drug scores), vae (variational autoencoder latent-space drug embeddings and reversal scores), faers (FDA Adverse Event Reporting System pharmacovigilance disproportionality results), mendelian_randomization (drug-target Mendelian randomization results for HMGCR against IPF), and validation (external validation results, including cross-cohort reproducibility on an independent held-out cohort, preclinical active-set enrichment, head-to-head comparison against the RGES state-of-the-art method, and permutation/bootstrap statistics). Raw input data are not redistributed here and remain available from their original sources, cited in the accompanying README: the NCBI Gene Expression Omnibus (GEO accessions listed per cohort), the LINCS L1000 platform, the STRING protein–protein interaction database, and the Global Biobank Meta-analysis Initiative. Analysis source code is available at https://github.com/NisargOza/TRACE-drug-repurposing.

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Categories

Drug Discovery, Transcriptomics, Computational Biology

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