Simulation study scenario algorithm on gene expression differences of Chickpea data in Indonesia to modeling series with the Bayesian approach

Abstract

Abstract Data on gene expression differences of chickpeas in Indonesia in healthy and diseased conditions was the result of microarray experiments. The diseased condition in chickpeas are caused by Ascochyta Rabiei pathogenic fungi. To learn more details about the gene expression differences data of chickpeas in Indonesia, especially regarding the distribution and fit modeling of the data, a specific simulation scenario is needed in order to obtain an overview of these data. The purpose of this study is to obtain the right simulation scenario algorithm for data on differences in gene expression of chickpeas in Indonesia in a series of modeling activities using the Bayesian approach. The results showed that with certain simulation scenarios obtained simulation data of gene expression differences of chickpeas in Indonesia that are similar to the original data. In this scenario repetition of 1,000 times with each repetition generated a data sample as many as 3 n according to the number of samples in the original data. These simulation scenario has specific characteristics because of the strict limitations of the meaning of the data on the gene expression differences that are generated. In these simulation scenario, the value of largest tolerance limit is 0.0999.