Summary: Recent studies have uncovered a strong effect of host genetic variation on the composition of host-associated microbiota. Here, we present HOMINID, a computational approach based on Lasso linear regression, that given host genetic variation and microbiome composition data, identifies host SNPs that are correlated with microbial taxa abundances. By using HOMINID on data from the Human Microbiome Project, we identified 2,127 human SNPs in which genetic variation is correlated with microbiome taxonomic composition in 15 body sites. We also present a tool for visualization of host-microbiome association network identified in HOMINID. Availability and implementation: Software and code are available at https://github.com/blekhmanlab/hominid, online visualization tool at http://z.umn.edu/genemicrobe.