DoEstRare

DoEstRare estimates variant position densities with a kernel method and performs rare variant association testing to detect clusters of disease risk variants and assess global allele frequency differences between cases and controls.

Key Features:

• Position Density Estimation: Estimates variant position densities within genomic regions using a kernel method weighted by allele frequencies.
• Cluster Detection and Frequency Analysis: Detects clusters of disease risk variants and assesses global allele frequency differences between cases and controls.
• Integration of Variant Position Information: Incorporates variant position information within protein sequences and inter-genic regulatory regions to relate location to disease susceptibility.
• Performance Evaluation: Evaluates type I error control and statistical power through extensive simulation studies and analyses of real datasets.

Scientific Applications:

• Rare Variant Association Studies: Applies to complex diseases where rare variants contribute to genetic architecture and complements existing association tests.
• Use-case Examples: Has been applied to datasets from Brugada syndrome and early-onset Alzheimer's disease to provide complementary insights.

Methodology:

Uses a kernel method for position density estimation weighted by allele frequencies, performs cluster detection and global allele frequency comparisons between cases and controls, and evaluates performance via simulation studies and analyses of real datasets.