Exploring GAPIT Package Features with Simulated Genomic Data

The agronomic information process in the genetics prospect currently presents voluminous data, which necessitates the continuous development of innovative and quality statistical methods that meet the Big Data era in which much is being reestablished in the form of generating, analyzing and absorbing data. The R language is an efficient tool for these types of analyzes and allows some structures and functionalities, such as the GAPIT package, which conducts genomic association (GWAS) and genomic prediction (GS). For this reason, this work aims at the study and exploration of characteristics of the GAPIT package, around a simulated data set. We demonstrate some output files that include graphical resources and tables ready for publication of results, identifying the GAPIT package as a viable alternative when working with large volumes of genotype data and obtaining quick and efficient responses.