Epigenome-wide association studies without the need for cell-type composition. ![]() FaST linear mixed models for genome-wide association studies. An example of FaST-LMM with cloud computing is here. Another version supporting corrections for cellular heterogeneity is available in python and R. A C++ version, including Windows binary, Linux binary, and source, supports univariate GWAS and limited epistatic testing. It supports univariate GWAS, tests for epistasis, corrections for cellular heterogeneity via the inclusion of principal components, set association tests, and heritability estimation. ![]() The most up-to-date version of FaST-LMM is written in python and available on GitHub. ![]() FaST-LMM runs on both Windows and Linux, and has been tested on data sets with over one million samples. Click here to download standard version of FaST-LMMįaST-LMM, (Factored Spectrally Transformed Linear Mixed Models) is a set of tools for efficiently performing genome-wide association studies (GWAS), prediction, and heritability estimation on large data sets. If you are interested in using this, please click here to send an email to with “GWAS use request” as the subject. ![]() If you are interested in reading about it, click here. NEW: Ludicrous speed LMM can run 1 million samples.Ī version of FaST-LMM has now been optimized for use in the cloud and cloud sized data.
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