NCBI GEO: archive for functional genomics data sets—update

By Tanya Barrett, Stephen E. Wilhite, Pierre Ledoux, Carlos Evangelista, Irene F. Kim, Maxim Tomashevsky, K. A. Marshall, Katherine H. Phillippy, Patti M. Sherman, Michelle Holko and 7 more. Nucleic Acids Res., 2012

9,594 citations recorded by the source corpus.

The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray and next-generation sequence functional genomic data sets submitted by the research community. The resource supports archiving of raw data, processed data and metadata which are indexed, cross-linked and searchable. All data are freely available for download in a variety of formats. GEO also provides several web-based tools and strategies to assist users to query, analyse and visualize data. This article reports current status and recent database developments, including the release of GEO2R, an R-based web application that helps users analyse GEO data.

Subfields: Molecular Biology

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Citations in the corpus

TISCH: a comprehensive web resource enabling interactive single-cell transcriptome visualization of tumor microenvironment (2020, methodology): “TISCH builds a scRNA-seq atlas of 76 high-quality tumor datasets across 27 cancer types, which were mainly collected from Gene Expression Om-nibus (GEO; 16) and ArrayExpress (17).”
Understanding multicellular function and disease with human tissue-specific networks (2015, neutral): “We defined T ′ for each tissue as genes specifically annotated to unrelated tissues.”
Database resources of the National Center for Biotechnology Information (2014, background): “The Epigenomics database provides displays (‘genome tracks’) of the raw data (stored in the GEO and SRA databases) mapped to genomic coordinates.”
Circular RNA cSMARCA5 inhibits growth and metastasis in hepatocellular carcinoma. (2018, methodology): “from a Chinese cohort (GSE14520, GPL3921)[37] using GEO2R[38].”
NONCODEV5: a comprehensive annotation database for long non-coding RNAs (2017, methodology): “Exosome-related RNA-seq data were collected from 6 RNA-sequencing datasets downloaded from the GEO database (Table 1).”
The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest (2022, methodology): “STRING collects gene expression evidence from RNA expression arrays and RNA-Seq datasets processed by the GEO database (65) as well as co-regulation evidence from the ProteomeHD database (7).”
Hierarchical cooperation of transcription factors from integration analysis of DNA sequences, ChIP-Seq and ChIA-PET data (2019, methodology): “The raw ChIA-PET sequence datasets for the K562, GM12878, MCF7, and HUVEC cell lines are down-loaded from the Gene Expression Omnibus (GEO) databases [45].”
starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq data (2013, methodology): “Integration of Ago and other RBP binding sites from published CLIP data HITS-CLIP, PAR-CLIP, iCLIP and CLASH data were retrieved from the Gene Expression Omnibus (22), the supplementary data of original references or directly from authors on request (Supplementary Table S1).”
CADD v1.7: using protein language models, regulatory CNNs and other nucleotide-level scores to improve genome-wide variant predictions (2024, background): “Tens of thousands of functional genomics data sets are available, for example through the NBCI Gene Expression Omnibus (GEO) ( 81 )—including gene expression, DNA accessibility, immunoprecipitation of DNA binding (transcription factors and histones), DNA methylation, 3D organization and interaction…”
Drug repositioning for non-small cell lung cancer by using machine learning algorithms and topological graph theory (2016, methodology): “The micro-array data for lung cancer were downloaded from GEO [24] and summarized in Table 1.”
The Database of Genomic Variants: a curated collection of structural variation in the human genome (2013, background): “Authors are encouraged to submit their raw data to the appropriate archive, either Gene Expression Omnibus (16) or Array Express (17) and processed variant calls to DGVa or dbVar.”
The harmonizome: a collection of processed datasets gathered to serve and mine knowledge about genes and proteins (2016, background): “GEO Signatures of DEGs for Diseases (56, 57)”