On this page:

• Class 0: Finishing up the SLE exercise.
• Class 1. ClusterProfiler GO term and gene set enrichment analysis.
• Class 2: Single-cell data analysis mini-project - CITE-seq.
• Optional (Advanced): WGCNA - Weighted gene co-expression network analysis.
  

Class 0: Finishing up the SLE exercise

Topics:

• Finishing up the DESeq portion of the SLE exercise
• Getting gene sets and saving them with all the related information to continue Week 2 exercises
• Follow the vignette provided in Google Drive,

Supporting material:

• Lab from Week 1: DESeq2 analysis mini-project.
• Illustrations of how dplyr functions work: By Allison Horst,

Homework:

• This is “03. Completing SLE mini project” in Gradescope
• Submit your completed PDF lab report with answers to homework questions at GradeScope,

Class 1. ClusterProfiler GO term and gene set enrichment analysis

Topics:

• Functional analysis of gene sets gathered from RNA-seq data
• GO term enrichment analysis vignette,
• Gene set enrichment analysis (GSEA) vignette,
• Weighted gene co-expression network analysis (WGCNA)

Supporting material:

• Slides: Large PDF,
• NYU Center For Genomics and Systems Biology: gene set analysis,
• ClusterProfiler documentation and tutorials: Yu Lab,

Homework:

• This is “04. GO term enrichment analysis” in Gradescope
• Submit your completed PDF lab report with answers to homework questions at GradeScope,

Class 2:Single-cell data analysis mini-project - CITE-seq

Topics:

• Analysis of single-cell RNA-seq data coupled with ADT (antibody derived tags) (i.e., CITE-seq) from 5k human PBMCs using Seurat
• Link to the exercise vignette,

Homework:

• This is “05. CITE-seq analysis” in Gradescope
• Submit your completed PDF lab report to GradeScope,