Keywords
Linear regression regularization, genome-wide association study (GWAS), LASSO
Abstract
The accurate estimation of the male flowering period in Maize crops is key for the prediction crop fertility. The recent scientific investigations has shown that the genetic single nucleotic polymorphism (SNP) can contribute in this regard. The genomewide association study (GWAS) is employed to generate these attributes (SNP). But it caused a high-dimensional data in which 4,981 observations with 7,389 SNP attributes. Hence, in this study, we used the penalized regression approach with the least absolute shrinkage and selection operator (Lasso) to reduce the dataset. In this regard, we set the regularization parameter to 0.21. It resulted in a set with 24 SNP markers to the predict of the days to anthesis (DtoA) in Maize plant
Course Name
STA 5703 Data Mining 1
Instructor Name
Rui Xie
College
College of Sciences
STARS Citation
Alipour Yengejeh, Amir, "Genome-Wide Association Study of The Maize Crop by The Lasso Regression Analysis" (2023). Data Science and Data Mining. 6.
https://stars.library.ucf.edu/data-science-mining/6
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