README.md

BBS-230B (2024)

Bulk RNA-seq, May 6th, 2024

Learning objectives

• Explain common considerations when designing a bulk RNA-seq experiment
• List the steps involved in the analysis of a bulk RNA-seq dataset
• Discuss common challenges and how to overcome them

Lessons

1. Experimental design (20 min)
2. Raw data to counts workflow (25 min)
3. Differential gene expression analysis (25 min)
4. Functional analysis (20 min)
5. Visualization of DE results (time permitting)

• Understanding PCA

Single cell RNA-seq, May 8th, 2024

Learning objectives

• Explain common considerations when designing a single-cell RNA-seq experiment
• List the steps involved in the analysis of a single cell dataset
• List the key statistical concepts utilized for the analysis

Lessons

• Single cell RNA-seq (50 mins)

Resources (bulk RNA-seq)

• bulk RNA-seq "Part I" (FASTQ to count matrix) workshop
• Differential Gene Expression analysis workshop
• Planning a successfull bulk RNA-seq experiment
• DESeq2 vignette
• Functional analysis visualization
• Ggplot2 for functional analysis

Resources (Single cell RNA-seq)

• Single-cell RNA-seq workshop
• "How many cells are needed per sample for my single-cell experiment?"
• http://bioconductor.org/books/release/OSCA/
• https://liulab-dfci.github.io/bioinfo-combio/
• https://hemberg-lab.github.io/scRNA.seq.course/
• https://github.com/SingleCellTranscriptomics
• Seurat vignettes

Resources (general)

• RMarkdown
• "Principal Component Analysis (PCA) clearly explained", a video from Josh Starmer