ArticleBioinformatics (Oxford, England)2024
PheWAS analysis on large-scale biobank data with PheTK.
Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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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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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.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Multi-ancestry genome-wide association analyses provide insights into the genetic basis of Hashimoto's thyroiditis.Nature genetics · 2026Pooled it
- Financial Toxicity Among Disaggregated Asian American Cancer Survivors.JAMA network open · 2026Article
- APOL1 risk alleles modulate T cell receptor signaling to promote allograft rejection.The Journal of clinical investigation · 2026Article
- A phenome-wide association study of rurality in theJAMIA open · 2026Article
- Shared trans-ancestry architecture of HLA-mediated disease risk in theResearch square · 2026Article
- DRIVE v3: Command Line Application for Identity-by-Descent Haplotype Clustering in Large Biobank Scale Data.Genetic epidemiology · 2026Article
- Shared trans-ancestry architecture of HLA-mediated disease risk in themedRxiv : the preprint server for health sciences · 2026Article
- Polygenic risk factors for comorbid diagnoses in individuals with substance use disorders: A phenome-wide survival analysis.Psychological medicine · 2026Article
- TACO1 regulates mitochondrial adaptation in hypertension-induced cardiac remodeling and heart failure.Research square · 2026Article
- The MICOS Complex Regulates Mitochondrial Structure and Oxidative Stress During Age-Dependent Structural Deficits in the Kidney.Aging cell · 2026Article
- Article
- 11 million days of longitudinal wearable data reveal novel future health insights.medRxiv : the preprint server for health sciences · 2026Article
- The effect of type 2 diabetes genetic predisposition on non-cardiovascular comorbidities.Nature communications · 2025Article
- Neurobeachin (NBEA) is a novel gene associated with GLP-1 receptor agonist associated weight loss.Diabetes, obesity & metabolism · 2025Article
- Metabolic reaction fluxes as amplifiers and buffers of risk alleles for coronary artery disease.Molecular systems biology · 2025Article
- The effect of type 2 diabetes genetic predisposition on non-cardiovascular comorbidities.medRxiv : the preprint server for health sciences · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
summaryWith the rapid growth of genetic data linked to electronic health record (EHR) data in huge cohorts, large-scale phenome-wide association study (PheWAS) have become powerful discovery tools in biomedical research. PheWAS is an analysis method to study phenotype associations utilizing longitudinal EHR data. Previous PheWAS packages were developed mostly with smaller datasets and with earlier PheWAS approaches. PheTK was designed to simplify analysis and efficiently handle biobank-scale data. PheTK uses multithreading and supports a full PheWAS workflow including extraction of data from OMOP databases and Hail matrix tables as well as PheWAS analysis for both phecode version 1.2 and phecodeX. Benchmarking results showed PheTK took 64% less time than the R PheWAS package to complete the same workflow. PheTK can be run locally or on cloud platforms such as the All of Us Researcher Workbench (All of Us) or the UK Biobank (UKB) Research Analysis Platform (RAP). AVAILABILITY AND IMPLEMENTATION: The PheTK package is freely available on the Python Package Index, on GitHub under GNU General Public License (GPL-3) at https://github.com/nhgritctran/PheTK, and on Zenodo, DOI 10.5281/zenodo.14217954, at https://doi.org/10.5281/zenodo.14217954. PheTK is implemented in Python and platform independent.
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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.