ArticleBioinformatics (Oxford, England)2019
deTS: tissue-specific enrichment analysis to decode tissue specificity.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 3 of them syntheses that pooled it.
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53 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Integrative genome-wide analysis unveils the genetic landscape of gallstone disease and highlights novel loci with therapeutic potential.BMJ open gastroenterology · 2025Pooled it
- Schizophrenia is associated with altered DNA methylation variance.Molecular psychiatry · 2025Pooled it
- A Review of Statistical Methods for Identifying Trait-Relevant Tissues and Cell Types.Frontiers in genetics · 2020Pooled it
- Dissecting the shared genetic architecture and biological mechanisms linking sleep traits and suicide attempts: from variants to genes.Molecular psychiatry · 2026Article
- Multidimensional 5-hydroxymethylcytosine features in cell-free DNA enable the detection, staging and subtyping of pancreatic ductal adenocarcinoma.Biomarker research · 2026Article
- Multi-omics uncovers the pleiotropic genetic mechanisms linking MASLD and cardiometabolic syndromes.Cardiovascular diabetology · 2026Article
- Cross-trait genomic and sequential analyses of multiple omics datasets identified shared genetic components for the gut-eye axis.Human genomics · 2026Article
- Tissue-Specific Extracellular Vesicles Enriched From Circulation: Exploring the Liquid Biopsy Perspective.Journal of extracellular biology · 2026Review
- GENEasso: a curated resource of credible disease-gene associations across complex diseases from GWAS summary statistics.Nucleic acids research · 2026Article
- Shared Genetic Susceptibility Between Asthma and Immune-Mediated Inflammatory Diseases.Canadian respiratory journal · 2026Article
- Multi-trait association analysis reveals shared genetic architecture between lung cancer and cardiometabolic diseases.iScience · 2025Article
- DEDUCE: statistical inference on disease-associated genes uncovers tissue-disease associations.NAR genomics and bioinformatics · 2025Article
- Spatiotemporal dynamics of RERE in schizophrenia pathogenesis: insights from multi-omics and single-cell sequencing.Schizophrenia (Heidelberg, Germany) · 2025Article
- Investigating the shared genetic architecture between adiposity measures and obesity-related cancers.Briefings in bioinformatics · 2025Article
- Unveiling genetic and biological links: exploring the intersection of autoimmune and psychiatric disorders.European journal of medical research · 2025Article
- A genome-wide cross-trait analysis characterizes the shared genetic architecture between lung and gastrointestinal diseases.Nature communications · 2025Article
- Integrated analysis for drug repositioning in migraine using genetic evidence and claims database.Frontiers in big data · 2025Article
- Genomic structural variations link multiple genes to bone mineral density in a multi-ethnic cohort study: Louisiana osteoporosis study.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2024Article
- The goldmine of GWAS summary statistics: a systematic review of methods and tools.BioData mining · 2024Article
- Genetic interactions and pleiotropy in metabolic diseases: Insights from a comprehensive GWAS analysis.Journal of cellular and molecular medicine · 2024Article
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4 authors.
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Abstract
motivationDiseases and traits are under dynamic tissue-specific regulation. However, heterogeneous tissues are often collected in biomedical studies, which reduce the power in the identification of disease-associated variants and gene expression profiles.
resultsWe present deTS, an R package, to conduct tissue-specific enrichment analysis with two built-in reference panels. Statistical methods are developed and implemented for detecting tissue-specific genes and for enrichment test of different forms of query data. Our applications using multi-trait genome-wide association studies data and cancer expression data showed that deTS could effectively identify the most relevant tissues for each query trait or sample, providing insights for future studies. AVAILABILITY AND IMPLEMENTATION: https://github.com/bsml320/deTS and CRAN https://cran.r-project.org/web/packages/deTS/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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