Differential Gene Expression Analysis

On the R platform (version 4.1.0; https://www.r-project.org/), the raw data were read using the read.maimages function of the limma package (23 (link)). Next, the raw data were background-subtracted using the backgroundCorrect function and normalized using the normalizeBetweenArrays function of the limma package. Quality reports were then generated using the arrayQualityMetrics package (24 (link)). Data outliers were detected using the distance between the arrays, and one sample, GSM2267025, was considered an outlier and therefore removed. The normalized data were further processed using the modelmatrix, makeContrasts, lmFit, eBayes, and topTable functions of the limma R package to obtain differentially expressed genes (DEGs) between the ND and HFD groups and between the wild-type (WT) and ob/ob mice. Genes with a fold change >1.5 and P value <0.05 were defined as DEGs.