Project Basic Statistics

Who is Dieu Nguyen

In this practical session, we continue working with the GSE161731 blood RNA-seq dataset from Lab 6 to investigate a biological question: **which genes are switched on or off in the blood of COVID-19 patients compared with healthy volunteers?** We will first use **principal component analysis (PCA)** to explore similarities and differences between samples and assess whether disease status is a major source of variation in the data. We will then use **DESeq2** to identify genes that are differentially expressed between COVID-19 and healthy samples, account for multiple testing across thousands of genes, and visualise the results using a **volcano plot, individual gene-expression plots, and a heatmap**.

Actividad_del_1er_50

In this practical session, you will work with the public GEO RNA-seq dataset GSE161731, which contains blood samples from patients with COVID-19, influenza, common-cold coronavirus infection, bacterial infection, and healthy volunteers. You will learn how to download and organise gene-count and patient metadata, ensure that samples are correctly matched, annotate Ensembl gene IDs with familiar gene symbols, and clean and explore cohort information. You will also perform basic checks using the RNA-seq data to validate sample characteristics and prepare clean, reproducible data objects for downstream analysis. By the end of the session, your dataset will be ready for PCA, quality control, and differential expression analysis in the next lab.