Differential-Expression-Analysis

Differential gene expression analysis of RNA-seq data from TCGA

Code: main.R

Result Files:

-Result

-Result with Significant Genes

-Result with Independent Hypothesis Weighting

Pairs plot

Principal Component Analysis

Heatmap visualization of some samples to get preliminary idea about the data

Hierarchial clustering Heatmap

Hierarchical clustering with heatmaps is used to assess the similarity in gene expression between the different samples in a dataset. This technique is used to explore how similar replicates are to each other and whether the samples belonging to different sample groups cluster separately. The heatmap is created by using the gene expression correlation values for all pairwise combinations of samples in the dataset, with the value 1 being perfect correlation. The hierarchical tree shows which samples are more similar to each other and the colors in the heatmap depict the correlation values

Dispersion estimate

Adding contrasts

LFC shrinkage

Expression heatmap - Subset normalized counts for significant genes

Volcano plot