ArticleNature communications2018
Massive mining of publicly available RNA-seq data from human and mouse.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 467 papers, 1 of them a synthesis that pooled it.
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
467 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Meta-Analysis of the Effects of Acute Sleep Deprivation on the Cortical Transcriptome in Rodent Models.Journal of sleep research · 2026Pooled it
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- The mitochondrial chaperone HSPD1 folds MTHFD2 independently of its co-chaperone HSPE1.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2026Article
- Multimodal learning enables chat-based exploration of single-cell data.Nature biotechnology · 2026Article
- Systems biology framework for the rational design of operational conditions for in vitro/in vivo translation of tissue models.Science advances · 2026Article
- Leveraging neural network models for drug repurposing: a case study on cardiac hypertrophy.Scientific reports · 2026Article
- A transcription factor regulatory atlas for activity inference and perturbation prediction.Nucleic acids research · 2026Article
- IsoformSwitchAnalyzeR v2: analysis of functional isoform changes in long-read and single-cell sequencing data.NAR genomics and bioinformatics · 2026Article
- Histological aging signatures for monitoring tissue-specific aging and disease.Nature medicine · 2026Article
- Article
- Transcriptome signatures for the identification of bevacizumab responders in ovarian cancer.Genome medicine · 2026Article
- GRNContext: an interactive web platform for contextualized gene regulatory networks visualization across human cancers.Bioinformatics (Oxford, England) · 2026Article
- SenFlag gene signature identifies senescent cells in mouse and human tissues through a conserved core transcriptional program.The EMBO journal · 2026Article
- Multimodal MRI combined with RNA sequencing reveals pathological signatures in the 9-month-old 3×Tg-AD mouse brain.Neural regeneration research · 2026Article
- A novel RNA-binding activity of ECD contributes to U5 snRNP stability and pre-mRNA splicing.Nucleic acids research · 2026Article
- ChEA-KG and ChEA-KG-TS: a network-based transcription factor enrichment analysis tool with an accompanying time-series workflow.Nucleic acids research · 2026Article
- Consensus Pituitary Atlas, a scalable resource for annotation, novel marker discovery, and analyses in mouse pituitary gland research.Cell reports · 2026Article
- Metabolic pathway signatures define prognostic subtypes of lung adenocarcinoma.Discover oncology · 2026Article
- The recount3 Python package for programmatic access to uniformly processed RNA-seq data.bioRxiv : the preprint server for biology · 2026Article
- Human XIRP1 is a new podosome protein targeting cytosolic bacteria as part of the IFN-γ defense program.Journal of immunology (Baltimore, Md. : 1950) · 2026Article
407 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
RNA sequencing (RNA-seq) is the leading technology for genome-wide transcript quantification. However, publicly available RNA-seq data is currently provided mostly in raw form, a significant barrier for global and integrative retrospective analyses. ARCHS4 is a web resource that makes the majority of published RNA-seq data from human and mouse available at the gene and transcript levels. For developing ARCHS4, available FASTQ files from RNA-seq experiments from the Gene Expression Omnibus (GEO) were aligned using a cloud-based infrastructure. In total 187,946 samples are accessible through ARCHS4 with 103,083 mouse and 84,863 human. Additionally, the ARCHS4 web interface provides intuitive exploration of the processed data through querying tools, interactive visualization, and gene pages that provide average expression across cell lines and tissues, top co-expressed genes for each gene, and predicted biological functions and protein-protein interactions for each gene based on prior knowledge combined with co-expression.
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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.