SBAT (Sparse Bayesian Association Testing)
A program for performing Genome-wide association testing with multiple, continuous traits in related samples, using a multi-trait mixed model framework.
SBAT implements 2 different models
- A full model – where a SNP has a non-zero effect on all the traits.
- A sparse model – where a SNP has a non-zero effect on a subset of the traits.
Both models use an EM algorithm for genetic and environmental covariance estimation as the first step. This provides very efficient inference that allows hundreds of traits to be analysed. The computational efficiency of this step is illustrated in the Figure below.
Software registration and license:
SBAT is freely available for academic use only.
If you have any questions about this software please post a message on the OXSTATGEN mail list.
If you use full model in SBAT please cite the following publications:
Elliott et al. (2017) The genetic basis of human brain structure and function: 1,262 genome-wide associations found from 3,144 GWAS of multimodal brain imaging phenotypes from 9,707 UK Biobank participants. (under review)
Andrew Dahl, Valentina Iotchkova, Amelie Baud, Åsa Johansson, Ulf Gyllensten, Nicole Soranzo, Richard Mott, Andreas Kranis, Jonathan Marchini. A multiple phenotype imputation method for genetic studies. Nature Genetics doi:10.1038/ng.3513
If you use the sparse model in SBAT please cite
Kevin Sharp, Valentina Iotchkova and Jonathan Marchini (2017) Sparse Bayesian Modelling for Multitrait Genetic Association Studies (in preparation)