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HOMINID

Python MPI program to identify associations between host genetic variation and microbiome taxonomic composition.

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 2,158 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.

Online visualization tool at http://z.umn.edu/genemicrobe

Contact: blekhmanlab@gmail.com

Running the HOMINID software

You'll want to read these documents, in order:

  1. Python software requirements
  2. Setting up the Python virtual environment
  3. Installation
  4. HOMINID analysis pipeline
  5. Running hominid on sample data
  6. Running hominid on your data
  7. Running hominid_stability_selection on your data
  8. Running hominid_sort_results on your data

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Hominid: host-microbiome interaction identification

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  • Python 96.1%
  • Shell 3.9%