Fig. 1

Data-analysis workflow. This study consisted of seven main block-steps: 1 The collection of public microarray information located at GEO (Gene Expression Omnibus) database with Python and R. 2 Raw data pre-processing and probe annotation. 3 Statistical data analysis with three different statistics to get the gene expression variability in adipose tissue samples of Hsa and Mmu, considering the biological sex as a variable. 4 Meta-analysis by Rank Product method. 5 Functional annotation with Gene Ontology (GO) terms. 6 GTEX-based gene expression filtering, to select potential reference genes suitable to compare both sexes in gene expression analyses. 7 Experimental validation by qPCR