ArticleBMC bioinformatics2020
SPECS: a non-parametric method to identify tissue-specific molecular features for unbalanced sample groups.
Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- TiSMeD: A tissue-specific methylation and expression database for biomarker and translational applications.Molecular therapy. Nucleic acids · 2026Article
- Patient-specific alterations in blood plasma cfRNA profiles enable accurate classification of cancer patients and controls.Communications medicine · 2026Article
- Atlas of nascent RNA transcripts reveals tissue-specific enhancer to gene linkages.BMC genomics · 2025Article
- Anti-HER2 therapy response assessment for guiding treatment (de-)escalation in early HER2-positive breast cancer using a novel deep learning radiomics model.European radiology · 2024Article
- Human skin specific long noncoding RNA HOXC13-AS regulates epidermal differentiation by interfering with Golgi-ER retrograde transport.Cell death and differentiation · 2023Article
- Sequence variation, common tissue expression patterns and learning models: a genome-wide survey of vertebrate ribosomal proteins.NAR genomics and bioinformatics · 2020Article
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Authors and funding
5 authors.
Funding
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Abstract
backgroundTo understand biology and differences among various tissues or cell types, one typically searches for molecular features that display characteristic abundance patterns. Several specificity metrics have been introduced to identify tissue-specific molecular features, but these either require an equal number of replicates per tissue or they can't handle replicates at all.
resultsWe describe a non-parametric specificity score that is compatible with unequal sample group sizes. To demonstrate its usefulness, the specificity score was calculated on all GTEx samples, detecting known and novel tissue-specific genes. A webtool was developed to browse these results for genes or tissues of interest. An example python implementation of SPECS is available at https://github.com/celineeveraert/SPECS. The precalculated SPECS results on the GTEx data are available through a user-friendly browser at specs.cmgg.be.
conclusionsSPECS is a non-parametric method that identifies known and novel specific-expressed genes. In addition, SPECS could be adopted for other features and applications.
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