R for Biological Data Analysis

Part 1 (R for Medical Data)

Overview

• Importing example "medical data" from a spreadsheet
• selecting columns
• restricting rows with filter
• summarising data, and grouping
• boxplots and bar plots
• "piping" to create short workflows

Pre-course package install

Please install the following packages before the course using the following code:-

install.packages(c("readr",
                  "dplyr",
                  "ggplot2",
                  "stringr",
                  "forcats"))

Pre-course downloads

Please download all these files and place in a folder that you wish to work in

• Example Data (tcga_clinical_CLEANED.tsv)
• Example Data 2 (tcga_clinical_MESSY.tsv)
• R Markdown

Materials

• HTML

Part 2 (R for omics analysis)

Overview

• Importing some RNA-sequencing counts
• Using PCA as QC diagnostic
• Differential expression to find statistically-significant genes
• Using databases to map between gene naming schemes
• Associating statistical findings with biological and clinical significance

Package Install

Please install the following packages before the course using the following code:-

install.packages("BiocManager")
BiocManager::install(c("SummarizedExperiment",
                      "tidybulk",
                      "org.Hs.eg.db",
                      "EnhancedVolcano",
                      "ggrepel"))

Download before the course

• Breast Cancer RNA-Seq counts
• Breast Cancer RNA-Seq metadata
• R Markdown

Rendered Materials

• HTML