Gene Expression Analysis: Quantifying and Comparing Gene Expression Levels in Cancer and Normal Samples

This study investigates gene expression changes in cancer samples. To quantify the expression level of each gene in each sample, the authors utilized a dataset from Wang et al.74 containing RNA-seq data from both tumor and control samples from TCGA, along with expression data from normal samples obtained from the GTEx consortium. The dataset underwent quantile-normalization and batch-correction using ComBat77. For each gene, differential expression was calculated as a log2 fold change between expression in cancer versus a matched normal sample. This differential expression was then averaged across samples. In cases where the expression of a gene was not measured in either the normal or the matched cancer type-specific samples, the expression omic value for that gene was not computed, and its missing value was set to zero.

Key Aspects of the Study:

• Data source: The study utilized a dataset from Wang et al. containing RNA-seq data from both tumor and control samples from TCGA, as well as expression data from normal samples from the GTEx consortium.
• Data normalization: The data was normalized and batch-corrected using ComBat77.
• Quantification of gene expression: The expression level of each gene in each sample was quantified.
• Differential expression analysis: Differential expression was computed as a log2 fold change between expression in cancer versus a matched normal sample, and then averaged across samples.
• Handling missing values: If the expression of a gene was not measured in either the normal or the matched cancer type-specific samples, the expression omic value for that gene was not computed, and its missing value was set to zero.