Summary of The Most Misunderstood Concept in bioinformatics

Mohammad Mobashir presented a detailed overview of Differentially Expressed Genes (DEG) analysis, emphasizing the need for a foundational understanding of basic concepts like P values and fold changes, and outlining the computational and experimental profiling methods used to identify statistically significant changes in gene expression. The presentation covered the key steps for DEG prediction, including data integration and normalization, the use of statistical tests like DESeq2 and EdgeR, and the interpretation of P values and log-to-fold changes for determining upregulated or downregulated genes. The speaker also explained the necessity of multiple testing correction via methods like the Benjamini-Hochberg procedure, the use of volcano plots for visualization, and the applications and advanced steps in DEG analysis, such as pathway and functional enrichment analysis.
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