📊 Complete 13-Chapter Curriculum
Bioconductor & Statistical Genomics
• From Foundations to DESeq2, ComplexHeatmap & Seurat
R for Next Gen Biologist
The definitive statistical computing and Bioconductor roadmap designed specifically for wet-lab scientists, bioinformaticians, and computational biologists. Master R from foundational vectors and data frames to high-throughput interval arithmetic with GenomicRanges, publication graphics with ggplot2, differential expression with DESeq2, clustered heatmaps with ComplexHeatmap, and single-cell transcriptomics with Seurat.
Download Chapter 1 R Script (.R)
Explore RNA-Seq & scRNA Pipelines →
15 standalone runnable .R scripts for course & genomics
Chapter 1
Foundations
1: Getting Started with R & RStudio
Chapter 2
Data Structures
2: R Data Structures & Factors
Chapter 3
Logic & Functions
3: Control Flow & Custom Functions
Chapter 4
Data Wrangling
4: Tidyverse Biological Wrangling
Chapter 5
Genomic File I/O
5: Biological File I/O & Formats
Chapter 6
Visualization
6: Publication Figures with ggplot2
Chapter 7
Bioconductor Core
7: Bioconductor Core & GenomicRanges
Chapter 8
Biostatistics
8: Statistical Hypothesis Testing
Chapter 9
Transcriptomics
9: Bulk RNA-Seq with DESeq2
Chapter 10
Clustering & Heatmaps
10: Omics Heatmaps & Clustering
Chapter 11
Functional Genomics
11: Pathway & GO Enrichment
Chapter 12
Single-Cell Omics
12: Single-Cell RNA-Seq with Seurat
Chapter 13
Capstone & Reproducibility