1.3.Differential Expression
Differential Expression for bulk RNAs
Pipeline
Data Structure
Inputs
Outputs
Running Scripts
Software/Tools
Assumption for most normalization and differential expression analysis tools: The expression levels of most genes are similar, i.e., not differentially expressed.
a) DEseq: defines scaling factor (also known as size factor) estimates based on a pseudoreferencesample, which is built with the geometric mean of gene counts across all cells (samples).
b) EdgeR (TMM): trimmed mean of M values
c) Wilcox Test using RPM: Read counts Per Million of total mapped reads; alternatives: RPKM, TPM
Performance:
Example of single case
Draw Plots
1. Heatmap for DESeq2 normalized count matrix
2. PCA analysis
3. MA plot
4. Distance between samples
5. Hierarchical clustering for differential expressed genes
Tips/Utilities
Homework and more
Identify differential expressed genes for other RNA types. between differential conditions, i.e. Normal Control (NC) V.S. HCC using three methods: edgeR, DESeq2 and Wilcox/Mann-Whitney-U Test.
Draw Venn plot to show the difference among the above three methods.
More Reading and Practice
Additional Tutorial : 3. Differential Expression Analysis
Video
1. Differential expression
Last updated