ArticleBioinformatics (Oxford, England)2017
MetaSRA: normalized human sample-specific metadata for the Sequence Read Archive.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 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
59 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Understanding the Nature of Metadata: Systematic Review.Journal of medical Internet research · 2022Pooled it
- Large-scale automated detection reveals pervasive sex imbalance in biomedical research.bioRxiv : the preprint server for biology · 2026Article
- CistromeMeta: a large language model powered tool for automated ChIP-seq metadata extraction.Bioinformatics (Oxford, England) · 2026Article
- Differential assembly of mouse and human tumor microenvironments.Nature immunology · 2026Article
- The Paipu framework enables creation of a large-scale mammalian cancer transcriptomics atlas.bioRxiv : the preprint server for biology · 2026Article
- Metappuccino: large language model-driven reconstruction of sequence read archive metadata for cancer research.Bioinformatics (Oxford, England) · 2026Article
- Transcriptomic data and biomedical literature synergize in finding pharmacologic gene regulators.bioRxiv : the preprint server for biology · 2026Article
- Using semantic search to find publicly available gene-expression datasets.Bioinformatics (Oxford, England) · 2026Article
- How far are we from the era of big data in transcriptomics? Lessons from the bacterial data in GEO.Briefings in bioinformatics · 2025Review
- A computational framework for extracting biological insights from SRA cancer data.Scientific reports · 2025Article
- Extraction of biological terms using large language models enhances the usability of metadata in the BioSample database.GigaScience · 2025Article
- Public Omics Explorer (POE): Enabling integrative semantic search across GEO omics datasets based on PubMed publications.Computational and structural biotechnology journal · 2025Article
- Annotating publicly-available samples and studies using interpretable modeling of unstructured metadata.Briefings in bioinformatics · 2024Article
- What is the real value of omics data? Enhancing research outcomes and securing long-term data excellence.Nucleic acids research · 2024Article
- 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
- The African Human Microbiome Portal: a public web portal of curated metagenomic metadata.Database : the journal of biological databases and curation · 2024Article
- Cistrome Data Browser: integrated search, analysis and visualization of chromatin data.Nucleic acids research · 2024Article
- Differential Expression Enrichment Tool (DEET): an interactive atlas of human differential gene expression.NAR genomics and bioinformatics · 2023Article
- Comprehensive Analysis of Ubiquitously Expressed Genes in Humans from A Data-driven Perspective.Genomics, proteomics & bioinformatics · 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
Abstract
motivationThe NCBI's Sequence Read Archive (SRA) promises great biological insight if one could analyze the data in the aggregate; however, the data remain largely underutilized, in part, due to the poor structure of the metadata associated with each sample. The rules governing submissions to the SRA do not dictate a standardized set of terms that should be used to describe the biological samples from which the sequencing data are derived. As a result, the metadata include many synonyms, spelling variants and references to outside sources of information. Furthermore, manual annotation of the data remains intractable due to the large number of samples in the archive. For these reasons, it has been difficult to perform large-scale analyses that study the relationships between biomolecular processes and phenotype across diverse diseases, tissues and cell types present in the SRA.
resultsWe present MetaSRA, a database of normalized SRA human sample-specific metadata following a schema inspired by the metadata organization of the ENCODE project. This schema involves mapping samples to terms in biomedical ontologies, labeling each sample with a sample-type category, and extracting real-valued properties. We automated these tasks via a novel computational pipeline. AVAILABILITY AND IMPLEMENTATION: The MetaSRA is available at metasra.biostat.wisc.edu via both a searchable web interface and bulk downloads. Software implementing our computational pipeline is available at http://github.com/deweylab/metasra-pipeline. CONTACT: cdewey@biostat.wisc.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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.