Learning interpretable models of phenotypes from whole genome sequences with the Set Covering Machine

Alexandre Drouin, Sébastien Giguère, Vladana Sagatovich +4

The increased affordability of whole genome sequencing has motivated its use for phenotypic studies. We address the problem of learning interpretable models for discrete phenotypes…