ArticleGigaScience2019
Digital expression explorer 2: a repository of uniformly processed RNA sequencing data.
Article in GigaScience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
47 citing papers in PubMed.
- Transcriptome signatures for the identification of bevacizumab responders in ovarian cancer.Genome medicine · 2026Article
- Lipogenesis-driven EGFR palmitoylation enables metastatic immune evasion in triple-negative breast cancer.bioRxiv : the preprint server for biology · 2026Article
- Transcriptomic Meta-Analysis as a Framework for Robust Cross-Study Biological Inference.International journal of molecular sciences · 2026Review
- Transcriptomic data and biomedical literature synergize in finding pharmacologic gene regulators.bioRxiv : the preprint server for biology · 2026Article
- The transcriptional regulatory network of the Escherichia coli MG1655 reference strain.Nucleic acids research · 2026Article
- Utilisation of Machine Learning Approaches Improves RNA-Seq Transcriptome Analyses in Alzheimer's Disease Brain.Journal of molecular neuroscience : MN · 2026Article
- CORESH: a gene signature-based search engine for public gene expression datasets.Nucleic acids research · 2025Article
- Extraction of biological terms using large language models enhances the usability of metadata in the BioSample database.GigaScience · 2025Article
- Suppression of thrombospondin-1-mediated inflammaging prolongs hematopoietic health span.Science immunology · 2025Article
- Human vascularized macrophage-islet organoids to model immune-mediated pancreatic β cell pyroptosis upon viral infection.Cell stem cell · 2024Article
- RummaGEO: Automatic mining of human and mouse gene sets from GEO.Patterns (New York, N.Y.) · 2024Article
- iModulonMiner and PyModulon: Software for unsupervised mining of gene expression compendia.PLoS computational biology · 2024Article
- Human Vascularized Macrophage-Islet Organoids to Model Immune-Mediated Pancreatic β cell Pyroptosis upon Viral Infection.bioRxiv : the preprint server for biology · 2024Article
- Article
- Interpretable online network dictionary learning for inferring long-range chromatin interactions.PLoS computational biology · 2024Article
- RummaGEO: Automatic Mining of Human and Mouse Gene Sets from GEO.bioRxiv : the preprint server for biology · 2024Article
- SARS-CoV-2 infection causes dopaminergic neuron senescence.Cell stem cell · 2024Article
- Two subtle problems with overrepresentation analysis.Bioinformatics advances · 2024Article
- Lung lymphatic endothelial cells undergo inflammatory and prothrombotic changes in a model of chronic obstructive pulmonary disease.Frontiers in cell and developmental biology · 2024Article
- A multi-scale expression and regulation knowledge base for Escherichia coli.Nucleic acids research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRNA sequencing (RNA-seq) is an indispensable tool in the study of gene regulation. While the technology has brought with it better transcript coverage and quantification, there remain considerable barriers to entry for the computational biologist to analyse large data sets. There is a real need for a repository of uniformly processed RNA-seq data that is easy to use.
findingsTo address these obstacles, we developed Digital Expression Explorer 2 (DEE2), a web-based repository of RNA-seq data in the form of gene-level and transcript-level expression counts. DEE2 contains >5.3 trillion assigned reads from 580,000 RNA-seq data sets including species Escherichia coli, yeast, Arabidopsis, worm, fruit fly, zebrafish, rat, mouse, and human. Base-space sequence data downloaded from the National Center for Biotechnology Information Sequence Read Archive underwent quality control prior to transcriptome and genome mapping using open-source tools. Uniform data processing methods ensure consistency across experiments, facilitating fast and reproducible meta-analyses.
conclusionsThe web interface allows users to quickly identify data sets of interest using accession number and keyword searches. The data can also be accessed programmatically using a specifically designed R package. We demonstrate that DEE2 data are compatible with statistical packages such as edgeR or DESeq. Bulk data are also available for download. DEE2 can be found at http://dee2.io.
Indexed as
Identifiers
What OpenQuestion holds
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.