GEC

GEC calculates the effective number of independent markers (M(e)) to adjust multiple testing and control the genome-wide type 1 error rate in genome-wide association studies (GWAS), implemented in Java.

Key Features:

• Effective marker estimation: Computes the effective number of independent markers (M(e)) to account for non-independence among SNPs caused by linkage disequilibrium (LD).
• Improved calculation method: Implements a robust and rapid computational method that increases precision and speed for estimating M(e).
• Platform and dataset evaluation: Systematically evaluates M(e) across 13 Illumina and Affymetrix genotyping arrays and reference datasets from the HapMap Project and the 1000 Genomes Project.
• P-value threshold derivation: Derives genome-wide p-value thresholds that control the type 1 error rate at a significance level of 0.05 for different arrays and datasets.
• Consideration of imputation and SNP resources: Accounts for effects of commercial genotyping microarrays, genotype-imputation algorithms, and extensive SNP databases on multiple testing.

Scientific Applications:

• Multiple testing correction in GWAS: Adjusts multiple testing and sets genome-wide significance thresholds for GWAS while accounting for LD and imputed variants.
• Benchmarking genotyping arrays: Provides empirical p-value thresholds for array-based studies, approximately 1×10^-7 for early commercial arrays and ~5×10^-8 for current or merged arrays.
• Reference-dataset thresholds: Establishes thresholds for common SNPs in the 1000 Genomes Project (~1×10^-8) and for common SNPs within genes (~5×10^-8).
• Impact assessment of LD and imputation: Evaluates how LD structure and genotype-imputation influence the effective number of independent tests in GWAS.

Methodology:

Calculates the effective number of independent markers (M(e)) using a robust, rapid computation method and systematically evaluates M(e) across specified genotyping arrays and reference datasets to derive p-value thresholds that control the genome-wide type 1 error rate at 0.05.