MULTIPOW

MULTIPOW calculates statistical power and evaluates multistage designs for joint and replication-based genome-wide association studies (GWAS) to inform sample allocation and genotyping strategies.

Key Features:

• Power calculations for joint and replication-based analyses: Performs power calculations for both joint analyses and replication-based approaches in multi-stage genetic association studies, including detection of modest effect sizes.
• Cost-effective multistage design support: Supports evaluation of multistage study designs that screen a subset of samples and subsequently genotype additional samples to optimize resource allocation for genome-wide arrays.
• Theoretical framework for study design: Implements a theoretical framework incorporating design principles for genetic association studies and considerations for fixed genome-wide and custom genotyping arrays.
• Contextual consideration of large-scale reference datasets: Acknowledges high-throughput genotyping contexts and reference data from the Human Genome Project and HapMap when assessing GWAS feasibility.
• Practical power computation tools: Provides computations to plan studies with adequate statistical power to distinguish genuine genetic associations from spurious correlations.

Scientific Applications:

• GWAS power estimation and study design: Estimates statistical power and informs sample allocation and genotyping strategies for genome-wide association studies (GWAS).
• Validation across study phases: Supports design and validation of genetic associations across joint and replication-based analyses in multistage studies.
• Cost optimization for genotyping: Enables evaluation of cost-effective genotyping strategies using fixed genome-wide and custom arrays.

Methodology:

Integrates theoretical design principles and the properties of fixed genome-wide and custom genotyping arrays to compute power for joint and replication-based analyses in multistage genetic association studies.