LSMM

LSMM (Latent Sparse Mixed Model) is an efficient statistical approach to integrating functional annotations with genome-wide association studies.

Reference: Jingsi Ming, Mingwei Dai, Mingxuan Cai, Xiang Wan, Jin Liu and Can Yang. LSMM: A statistical approach to integrating functional annotations with genome-wide association studies. Bioinformatics. 2018. [Bioinformatics link]

• The R package 'LSMM' on github. The R package 'LSMM' provides model parameter estimation as well as statistical inference.
• The source code for simulation studies in the paper [github].
• The data sets analyzed in this paper can be download here, including nine genic category annotations, 127 cell-type specific functional annotations, and the summary statistics of 30 GWAS [download]

The disease-tissue relevance map inferred by LSMM