ArticleJournal of integrative bioinformatics2024
TidyGEO: preparing analysis-ready datasets from Gene Expression Omnibus.
Article in Journal of integrative bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The trial behind it
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Who cites it
9 citing papers in PubMed.
- Guidelines to Study Transcriptome Remodeling by Proteins Using Deep Sequencing (RNA-Seq).Methods in molecular biology (Clifton, N.J.) · 2027Article
- Vitiligo Information Resource database v3.NPJ systems biology and applications · 2026Article
- The AhR-TLR4 axis in non-IgE-mediated Cow's milk allergy: a systematic review with integrated multi-omics corroboration.Frontiers in allergy · 2026Review
- Bioinformatics analysis of glycolysis-related differentially expressed genes (GRDEGs) and their significance in ischemic stroke.Medicine · 2025Article
- Single-cell RNA sequencing reveals key signaling pathways and biological functions in giant cell tumors of bone.Discover oncology · 2025Article
- Public Omics Explorer (POE): Enabling integrative semantic search across GEO omics datasets based on PubMed publications.Computational and structural biotechnology journal · 2025Article
- RummaGEO: Automatic mining of human and mouse gene sets from GEO.Patterns (New York, N.Y.) · 2024Article
- RummaGEO: Automatic Mining of Human and Mouse Gene Sets from GEO.bioRxiv : the preprint server for biology · 2024Article
- AI-based prediction of drug-gene interactions modulating tight junction integrity: A deep learning framework highlighting multiple therapeutic targets.Journal of oral biology and craniofacial researchArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
TidyGEO is a Web-based tool for downloading, tidying, and reformatting data series from Gene Expression Omnibus (GEO). As a freely accessible repository with data from over 6 million biological samples across more than 4000 organisms, GEO provides diverse opportunities for secondary research. Although scientists may find assay data relevant to a given research question, most analyses require sample-level annotations. In GEO, such annotations are stored alongside assay data in delimited, text-based files. However, the structure and semantics of the annotations vary widely from one series to another, and many annotations are not useful for analysis purposes. Thus, every GEO series must be tidied before it is analyzed. Manual approaches may be used, but these are error prone and take time away from other research tasks. Custom computer scripts can be written, but many scientists lack the computational expertise to create such scripts. To address these challenges, we created TidyGEO, which supports essential data-cleaning tasks for sample-level annotations, such as selecting informative columns, renaming columns, splitting or merging columns, standardizing data values, and filtering samples. Additionally, users can integrate annotations with assay data, restructure assay data, and generate code that enables others to reproduce these steps.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.