CORESH: a gene signature-based search engine for public gene expression datasets

Public data repositories like Gene Expression Omnibus (GEO) contain an extensive amount of data from hundreds of thousands of experiments, making them a valuable resource for researchers. A common scenario for utilizing this resource is to show transcriptional similarity of one's own data to a public dataset as evidence of potentially similar biology. However, when searching for such datasets, researchers are usually limited to keyword-based search, which requires having a specific hypothesis and relies on the presence of high-quality metadata in public datasets. Here, we introduce CORESH, a web server designed to systematically find GEO datasets that match a user-provided gene signature-such as a list of top upregulated genes in response to a treatment-in a data-driven manner. CORESH operates on a compendium of >40 000 human and 40 000 mouse datasets and outputs a ranked list of datasets where the input genes exhibit similar expression patterns. The discovered datasets can then be used to identify experimental conditions associated with the activation of the query signature, offering insights into underlying biological mechanisms and guiding experimental validation. CORESH is freely accessible at https://alserglab.wustl.edu/coresh/, requires no login, and is regularly updated with the latest GEO data.

Authors

Institutions

Publication Details

Journal
Nucleic Acids Research
Published
2025-05-05
DOI
https://doi.org/10.1093/nar/gkaf372
Primary Topic
Gene expression and cancer classification
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

CORESH: a gene signature-based search engine for public gene expression datasets

Aigul Nugmanova, Vladimir Sukhov, Alexey Sergushichev, Parul Mehrotra et al.
Nucleic Acids Research
Gene expression and cancer classification
article

CORESH: a gene signature-based search engine for public gene expression datasets

Aigul Nugmanova, Vladimir Sukhov, Alexey Sergushichev, Parul Mehrotra, Maksim Kleverov, Maxim N. Artyomov, Kodi S. Ravichandran, Yury Vorontsov
article en

Abstract

Public data repositories like Gene Expression Omnibus (GEO) contain an extensive amount of data from hundreds of thousands of experiments, making them a valuable resource for researchers. A common scenario for utilizing this resource is to show transcriptional similarity of one's own data to a public dataset as evidence of potentially similar biology. However, when searching for such datasets, researchers are usually limited to keyword-based search, which requires having a specific hypothesis and relies on the presence of high-quality metadata in public datasets. Here, we introduce CORESH, a web server designed to systematically find GEO datasets that match a user-provided gene signature-such as a list of top upregulated genes in response to a treatment-in a data-driven manner. CORESH operates on a compendium of >40 000 human and 40 000 mouse datasets and outputs a ranked list of datasets where the input genes exhibit similar expression patterns. The discovered datasets can then be used to identify experimental conditions associated with the activation of the query signature, offering insights into underlying biological mechanisms and guiding experimental validation. CORESH is freely accessible at https://alserglab.wustl.edu/coresh/, requires no login, and is regularly updated with the latest GEO data.

Nucleic Acids ResearchVol. 53(W1)
ITMO University (RU), Washington University in St. Louis (US), Ghent University (BE), VIB-UGent Center for Inflammation Research (BE), Indian Institute of Technology Delhi (IN)
Washington University in St. Louis, Ministry of Science and Higher Education of the Russian Federation
Openalex Percentile: Top 91%
Gene expression and cancer classification
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.