LDAK includes tools for testing predictors both individually and jointly for association with a phenotype, and for clumping the results from these analyses.
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Single-Predictor Analysis explains how to perform linear regression (either classical or mixed-model) and logistic regression (only classical).
Gene-Based Analysis explains the general framework for testing sets of predictors for association using either individual-level data or summary statistics; these sets typically correspond to genes, but can instead be arbitrary chunks of the genome.
LDAK-GBAT focuses on gene-based association testing using summary statistics from single-SNP analysis and a reference panel.
Clumping is used to process the results from association testing (e.g., to determine the number of approximately independent significant loci or to prioritise loci for follow up).
