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Exercise 2 - R Programming
STA250 Exercise 2: R programming exercises covering data frames and basic data analysis.
Finding public RNA-seq data, annotating genes, and exploring counts and metadata
This lab introduces a practical workflow for working with public RNA-seq data in R. Using the GSE161731 whole-blood dataset from the Gene Expression Omnibus (GEO), we retrieve the raw count matrix and its sample metadata, align the two, and convert Ensembl gene identifiers into gene symbols. The lab then covers cleaning and verification of clinical metadata, descriptive statistics and the appropriate test for each variable type, the calculation and interpretation of CPM and TPM, and the gene-level expression plots and gene-set heatmaps used to inspect biologically selected marker genes. The dataset compares patients with COVID-19, influenza, seasonal coronavirus and bacterial infection against healthy controls, so the expected interferon and neutrophil signatures serve throughout as a positive control for the analysis.