ArticleGenome biology2020
PTWAS: investigating tissue-relevant causal molecular mechanisms of complex traits using probabilistic TWAS analysis.
Article in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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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
52 citing papers in PubMed, 70 citations in OpenAlex.
- Identifying causal genetic variants for high-altitude adaptation through blood eQTL analysis in plateau populations.Communications biology · 2026Article
- Genetic Correlation and Causal Inference Between Female Fat Distribution and Preeclampsia: An Integrative Genomic Study.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Higher eQTL power reveals signals that boost GWAS colocalization.American journal of human genetics · 2026Article
- Transcriptome-wide association study of prostate cancer in the Chinese population.Asian journal of urology · 2026Article
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- Integrative Omics Defines Metabolic Biomarkers and Genetic Regulatory Mechanisms of Mortality Risk.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Higher eQTL power reveals signals that boost GWAS colocalization.bioRxiv : the preprint server for biology · 2025Article
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- Genetic and functional analysis of unproductive splicing using LeafCutter2.bioRxiv : the preprint server for biology · 2025Article
- Elucidating shared genetic association between female body mass index and preeclampsia.Communications biology · 2025Article
- Multi-INTACT: integrative analysis of the genome, transcriptome, and proteome identifies causal mechanisms of complex traits.Genome biology · 2025Article
- Enhancing disease risk gene discovery by integrating transcription factor-linked trans-variants into transcriptome-wide association analyses.Nucleic acids research · 2025Article
- scTWAS Atlas: an integrative knowledgebase of single-cell transcriptome-wide association studies.Nucleic acids research · 2025Article
- regionalpcs improve discovery of DNA methylation associations with complex traits.Nature communications · 2025Article
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- The goldmine of GWAS summary statistics: a systematic review of methods and tools.BioData mining · 2024Article
- Inferring causal direction between two traits using RAmerican journal of human genetics · 2024Article
- Genotype × environment interactions in gene regulation and complex traits.Nature genetics · 2024Review
- An overview of detecting gene-trait associations by integrating GWAS summary statistics and eQTLs.Science China. Life sciences · 2024Review
- Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
We propose a new computational framework, probabilistic transcriptome-wide association study (PTWAS), to investigate causal relationships between gene expressions and complex traits. PTWAS applies the established principles from instrumental variables analysis and takes advantage of probabilistic eQTL annotations to delineate and tackle the unique challenges arising in TWAS. PTWAS not only confers higher power than the existing methods but also provides novel functionalities to evaluate the causal assumptions and estimate tissue- or cell-type-specific gene-to-trait effects. We illustrate the power of PTWAS by analyzing the eQTL data across 49 tissues from GTEx (v8) and GWAS summary statistics from 114 complex traits.
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Registered trials
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