ArticleBMC bioinformatics2016
SurvivalGWAS_Power: a user friendly tool for power calculations in pharmacogenetic studies with "time to event" outcomes.
Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 7 citations in OpenAlex.
- Article
- Genomic architecture and prediction of censored time-to-event phenotypes with a Bayesian genome-wide analysis.Nature communications · 2021Article
- pwrEWAS: a user-friendly tool for comprehensive power estimation for epigenome wide association studies (EWAS).BMC bioinformatics · 2019Article
- SurvivalGWAS_SV: software for the analysis of genome-wide association studies of imputed genotypes with "time-to-event" outcomes.BMC bioinformatics · 2017Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPower calculators are currently available for the design of genetic association studies of binary phenotypes and quantitative traits, but not for "time to event" outcomes, which are of particular relevance in pharmacogenetics. With the rapid emergence of pharmacogenetic association studies of single nucleotide polymorphisms (SNPs), and the complexity of clinical outcomes they consider, there is a need for software to perform power calculations of time to event data over a range of design scenarios and analytical methodologies.
resultsWe have developed the user friendly software tool SurvivalGWAS_Power to perform power calculations for time to event outcomes over a range of study designs and different analytical approaches. The software calculates the power to detect SNP association with a time to event outcome over a range of study design scenarios. The software enables analyses under a Cox proportional hazards model or Weibull regression model, and can account for treatment and SNP-treatment interaction effects. Simulated data sets can also be generated by SurvivalGWAS_Power to enable analyses with methods that are not currently supported by the power calculator, thereby increasing the flexibility of the software.
conclusionsSurvivalGWAS_Power addresses the need for flexible and user-friendly software for power calculations for genetic association studies of time to event outcomes, with particular design features of relevance in pharmacogenetics.
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Registered trials
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