Kover

From UFRC
Jump to navigation Jump to search

Description

kover website  

Kover is an out-of-core implementation of rule-based machine learning algorithms that has been tailored for genomic biomarker discovery. It produces highly interpretable models, based on k-mers, that explicitly highlight genotype-to-phenotype associations.

Environment Modules

Run module spider kover to find out what environment modules are available for this application.

System Variables

  • HPC_KOVER_DIR - installation directory
  • HPC_KOVER_BIN - executable directory




Citation

If you publish research that uses kover you have to cite it as follows:

Drouin, A., Letarte, G., Raymond, F., Marchand, M., Corbeil, J., & Laviolette, F. (2019). Interpretable genotype-to-phenotype classifiers with performance guarantees. Scientific Reports, 9(1), 4071.

Drouin, A., Giguère, S., Déraspe, M., Marchand, M., Tyers, M., Loo, V. G., Bourgault, A. M., Laviolette, F. & Corbeil, J. (2016). Predictive computational phenotyping and biomarker discovery using reference-free genome comparisons. BMC Genomics, 17(1), 754.