Figure 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 Products. 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.