lrgpr is a high-peformance, user-friendly R interface for evaluating linear mixed models. This package is designed for interactive, exploratory analysis of large genome-wide assocation studies (GWAS) using linear mixed models to account for the confounding effects of kinship and population structure.

The package also provides simple interfaces for standard (i.e. fixed effects) linear and logistic regression models. It allows fitting millions of regression models on a desktop computer by using an efficient implementation, parallelization and out-of-core computing for datasets that are too large to fit in main memory.

• Installation instructions: how to install dependencies (essential)
• Download package: v0.1.12


• Tutorial: thorough demonstration of the functionality and applications of lrgpr
• Manual: details about available functions


• Version information: details of updates in the current version
• Project summary page


• FAQ: see end of Tutorial


• Citation:
Hoffman, G.E., Mezey, J.G., Schadt, E.E. (2014) lrgpr: Interactive linear mixed model analysis of genome-wide association studies with composite hypothesis testing and regression diagnostics in R. Bioinformatics. 30 (21): 3134-3135. doi:10.1093/bioinformatics/btu435
• Related work:
Hoffman, G.E. (2013) Correcting for Population Structure and Kinship Using the Linear Mixed Model: Theory and Extensions. PLoS ONE 8(10): e75707. doi:10.1371/journal.pone.0075707