powerEQTL

powerEQTL calculates sample size and statistical power for expression quantitative trait locus (eQTL) analyses in bulk tissue and single-cell RNA sequencing studies to assess associations between genetic variants, such as single nucleotide polymorphisms (SNPs), and gene expression.

Key Features:

• Implementation: Implemented as an R package providing functions for eQTL power and sample size calculations.
• Statistical models: Supports ANOVA and simple linear regression models for eQTL analyses.
• Data types: Provides tailored functions for both bulk tissue and single-cell RNA-seq eQTL analyses.
• Calculations: Computes statistical power, minimal sample size, and detectable minor allele frequency for specified study parameters.
• Input parameters: Accepts allele frequency, effect size, and desired power level as inputs for calculations.
• SNP–phenotype association: Assesses associations between a single nucleotide polymorphism (SNP) and continuous phenotypes.

Scientific Applications:

• eQTL study design: Determines required sample sizes and power for planned eQTL experiments.
• Post-GWAS interpretation: Aids evaluation of causal links between GWAS-identified variants and gene expression via eQTL mapping.
• Single-cell RNA-seq planning: Supports power and sample size determination in single-cell RNA-seq studies where variability and design complexity affect detectability.
• SNP–phenotype studies: Facilitates planning of studies assessing associations between SNPs and continuous phenotypes.

Methodology:

Performs power and sample size calculations using ANOVA and simple linear regression models to compute power, minimal sample size, or detectable minor allele frequency from inputs including allele frequency, effect size, and desired power for bulk and single-cell eQTL analyses.