ArticleDatabase : the journal of biological databases and curation2013
Uncovering hidden duplicated content in public transcriptomics data.
Article in Database : the journal of biological databases and curation, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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Who cites it
7 citing papers in PubMed.
- The Bgee suite: integrated curated expression atlas and comparative transcriptomics in animals.Nucleic acids research · 2021Article
- Quality Matters: Biocuration Experts on the Impact of Duplication and Other Data Quality Issues in Biological Databases.Genomics, proteomics & bioinformatics · 2020Article
- BioDataome: a collection of uniformly preprocessed and automatically annotated datasets for data-driven biology.Database : the journal of biological databases and curation · 2018Article
- Benchmarks for measurement of duplicate detection methods in nucleotide databases.Database : the journal of biological databases and curation · 2017Article
- The neXtProt knowledgebase on human proteins: 2017 update.Nucleic acids research · 2017Article
- The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases.Nucleic acids research · 2016Article
- BgeeDB, an R package for retrieval of curated expression datasets and for gene list expression localization enrichment tests.F1000Research · 2016Article
Corrections and comments
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Authors and funding
5 authors.
Funding
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Abstract
As part of the development of the database Bgee (a dataBase for Gene Expression Evolution), we annotate and analyse expression data from different types and different sources, notably Affymetrix data from GEO and ArrayExpress, and RNA-Seq data from SRA. During our quality control procedure, we have identified duplicated content in GEO and ArrayExpress, affecting ∼14% of our data: fully or partially duplicated experiments from independent data submissions, Affymetrix chips reused in several experiments, or reused within an experiment. We present here the procedure that we have established to filter such duplicates from Affymetrix data, and our procedure to identify future potential duplicates in RNA-Seq data.
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Registered trials
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