Chronic Kidney Disease (CKD) Phenotype and Its Association with Single Nuclotide Polymorpisms (SNPs) using Elastic Net Method - Angga Aditya Permana, Analekta Tiara Perdana, Maureen Zerlina Oktaviani (International Journal of Intelligent Systems and Applications in Engineering, 2024)
Chronic kidney disease (CKD) is one of critical disorders that typically has no symptoms until late stages. Early intervention in its initial stages can delay this disease progression. Single nucleotide polymorphism (SNP) can be used as a genetic variation that can be observed with CKD phenotype. Association study of SNP and CKD phenotype needs assistance from a machine learning algorithm that can process data with many dimensions. In this research, Elastic Net used as a method to associate SNP with phenotype for CKD. Based on the result, it showed that the Elastic Net method can select 88 significant SNP with a low MAE score that is 0.755 with a good explained variance (R2) which is 0.999. Also, there are significant SNP that were chosen with Elastic Net method such as Rhd, F2, Col1a1, Nos3, F5, Gypc, F8, F10, Bcam, Rbp4, Plg, Thpo, Myh9, Akt1, Fgb, and F7.