# Introduction to Differential Gene Expression Analysis## Learning Objectives- Explain and interpret QC on count data using Principal Component Analysis (PCA) and hierarchical clustering- Implement DESeq2 to obtain a list of significantly different genes- Perform functional analysis on gene lists with R-based tools## Installations[Follow the instructions linked here](../index.html#installation-requirements) to download R and RStudio + Install Packages from CRAN and Bioconductor## Lessons### Part 1 (Getting Started)1. [Workflow (raw data to counts)](./01a_RNAseq_processing_workflow.html)1. [Experimental design considerations](./experimental_planning_considerations.html)1. [Intro to DGE / setting up DGE analysis](./01b_DGE_setup_and_overview.html)***### Part II (QC and setting up for DESeq2)1. [RNA-seq counts distribution](./01c_RNAseq_count_distribution.html)1. [Count normalization](./02_DGE_count_normalization.html)1. [Sample-level QC](./03_DGE_QC_analysis.html) (PCA and hierarchical clustering)1. [Design formulas](./04a_design_formulas.html)1. [Hypothesis testing and multiple test correction](./05a_hypothesis_testing.html)***### Part III (DESeq2)1. [Description of steps for DESeq2](./04b_DGE_DESeq2_analysis.html)1. [Wald test results](./05b_wald_test_results.html)1. [Summarizing results and extracting significant gene lists](./05c_summarizing_results.html)1. [Visualization](./06_DGE_visualizing_results.html)1. [Likelihood Ratio Test results](./08a_DGE_LRT_results.html)1. [Time course analysis](./08b_time_course_analyses.html)***### Part IV (Functional Analysis)1. [Gene annotation](./genomic_annotation.html)1. [Functional analysis - over-representation analysis](./10_FA_over-representation_analysis.html)1. [Functional analysis - functional class scoring / GSEA](./11_FA_functional_class_scoring.html)***[Workflow Summary](./07_DGE_summarizing_workflow.html)***## Building on this workshop* [Single-cell RNA-seq workshop](https://hbctraining.github.io/scRNA-seq/)* [RMarkdown](https://hbctraining.github.io/Training-modules/Rmarkdown/)* [Ggplot2 for functional analysis](https://hbctraining.github.io/Training-modules/Tidyverse_ggplot2/lessons/ggplot2.html)## Resources* [DESeq2 vignette](http://bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#theory-behind-deseq2)* GitHub book on [RNA-seq gene level analysis](http://genomicsclass.github.io/book/pages/rnaseq_gene_level.html)* [Bioconductor support site](https://support.bioconductor.org/t/deseq2/) (posts tagged with `deseq2`) * [Functional analysis visualization](https://yulab-smu.top/biomedical-knowledge-mining-book/enrichplot.html)