This lecture covers the quality control tools used in genomic data analysis, focusing on Affymetrix QA/QC, sample preparation QC, data QC, spike-ins, controls, and MAS 5 algorithms. It explains the importance of quality metrics, RMA-QC, and the RMA additive model for gene expression. The instructor discusses the challenges with quality measures and the robustness of the analysis, emphasizing the need for robust procedures in the presence of outliers and image artifacts.