Deng, E. Z. | Search bioRxiv

bioRxiv2024

RummaGEO: Automatic Mining of Human and Mouse Gene Sets from GEO

The Gene Expression Omnibus (GEO) is a major open biomedical research repository for transcriptomics and other omics datasets. It currently contains millions of gene expression samples from tens of thousands of studies collected by many biomedical research laboratories from around the world. While users of the GEO repository can search the metadata describing studies for locating relevant datasets, there are currently no methods or resources that facilitate global search of GEO at the data level. To address this shortcoming, we developed RummaGEO, a webserver application that enables gene expression signature search of a large collection of human and mouse RNA-seq studies deposited into GEO. To develop the search engine, we performed offline automatic identification of sample conditions from the uniformly aligned GEO studies available from ARCHS4. We then computed differential expression signatures to extract gene sets from these studies. In total, RummaGEO currently contains 135,264 human and 158,062 mouse gene sets extracted from 23,395 GEO studies. Next, we analyzed the contents of the RummaGEO database to identify statistical patterns and perform various global analyses. The contents of the RummaGEO database are provided as a web-server search engine with signature search, PubMed search, and metadata search functionalities. Overall, RummaGEO provides an unprecedented resource for the biomedical research community enabling hypothesis generation for many future studies. The RummaGEO search engine is available from: https://rummageo.com/.

bioinformatics↗

bioRxiv2023

Rummagene: Mining Gene Sets from Supporting Materials of PMC Publications

Every week thousands of biomedical research papers are published with a portion of them containing supporting tables with data about genes, transcripts, variants, and proteins. For example, supporting tables may contain differentially expressed genes and proteins from transcriptomics and proteomics assays, targets of transcription factors from ChIP-seq experiments, hits from genome-wide CRISPR screens, or genes identified to harbor mutations from GWAS studies. Because these gene sets are commonly buried in the supplemental tables of research publications, they are not widely available for search and reuse. Rummagene, available from https://rummagene.com, is a web server application that provides access to hundreds of thousands human and mouse gene sets extracted from supporting materials of publications listed on PubMed Central (PMC). To create Rummagene, we first developed a softbot that extracts human and mouse gene sets from supporting tables of PMC publications. So far, the softbot has scanned 5,448,589 PMC articles to find 121,237 articles that contain 642,389 gene sets. These gene sets are served for enrichment analysis, free text, and table title search. Users of Rummagene can submit their own gene sets to find matching gene sets ranked by their overlap with the input gene set. In addition to providing the extracted gene sets for search, we investigated the massive corpus of these gene sets for statistical patterns. We show that the number of gene sets reported in publications is rapidly increasing, containing both short sets that are highly enriched in highly studied genes, and long sets from omics profiling. We also demonstrate that the gene sets in Rummagene can be used for transcription factor and kinase enrichment analyses, and for gene function predictions. By combining gene set similarity with abstract similarity, Rummagene can be used to find surprising relationships between unexpected biological processes, concepts, and named entities. Finally, by overlaying the Rummagene gene set space with the Enrichr gene set space we can discover areas of biological and biomedical knowledge unique to each resource.

bioinformatics↗