A comparison of methods for interpreting random forest models of genetic association in the presence of non-additive interactions
Abstract Background Non-additive interactions among genes are frequently associated with a number of phenotypes, including known complex diseases such as Alzheimer’s, diabetes, and cardiovascular disease. Detecting interactions requires careful selection of analytical methods, and some machine learn...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2021-01-01
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| Series: | BioData Mining |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13040-021-00243-0 |