Power/sample size calculation software tools | Genome-wide association study data analysis
Statistical power calculations are crucial in designing genetic association studies. They help guide tradeoffs between large sample sizes and detailed assessments of genotype and phenotype, help determine which studies are viable, and help interpret research findings. Power/sample size calculation software tools are used for diverse data sets to evaluate optimal sample size and for statistical analysis of genetic associations.
Permits to calculate required sample size and power for genetic studies. Quanto is a program that computes sample size or power for association studies of genes, gene-environment interaction, or gene-gene interaction. A graphical interface allows users to change the model and to view results without editing the input file and rerun the program for every model.
Permits calculation of genome wide association studies (GWAS) with quantitative traits. GWAPower allows genetic researchers to use the genetic term, heritability, instead of the general statistical term, ‘phenotype means of each genotype’, in power calculations. It can be used for general genetic studies if researchers wish to use heritability as the parameter for genetic effect size. The tool ignores some complicating factors such as population stratification, various interactions among genetic variants, and environmental factors.
Estimates sample size for case-control association studies. OSSE is sample size estimator determines the necessary sample size in the setting of a pilot study, with unknown actual minor allele frequencies. The base values are set for the conventionally used significance level of 5% at 80% power. User can choose to calculate significance level or power instead by providing the other variables.
Implements a general pilot data-based method for power and sample size determination for high-dimensional genomic data. SSPA allows users to read data as a vector of test statistics and to process the desired estimates. This software offers functions to ease interpretation of results. It can deal with any type of test statistic distribution family so long as both null and alternative are known.
Provides a method for analyze metabolic phenotyping data sets. Statistical Power Analysis tool is a standalone software available in both Python and Matlab language. The application first models the distribution of pilot study data, and then introduces an artificial effect for finally deriving estimates and confidence intervals for performance metrics. The method is suited for large population studies performed with standardized protocols.
Explores and analyzes genetic data. Hail can generate variant annotations like call rate, Hardy-Weinberg equilibrium p-value, and population-specific allele count, generate sample annotations like mean depth, imputed sex, and TiTv ratio. It can find Mendelian violations in trios, analyze genetic similarity between samples via the GRM and IBD matrix, and compute sample scores and variant loadings using PCA. The software performs association analyses with phenotypes and covariates using linear and logistic regression.