NGS can provide the complete expression profile for the RNA in your samples. Differential expression analysis is valuable if you are investigating Total RNA giving you a complete expression profile for RNA species longer than 200 nucleotides, and if you are investigating RNA species of short length such as miRNAs.
Differential expression is a comparative method that provides relative values for the change in individual RNA molecules between two or more groups of samples (e.g. "treatment" and "control"). Because the result is a list of the changes in all RNAs between your two groups, it is a strong tool for exploratory studies with no pre-defined molecule of interest
OUTPUT FROM STANDARD DIFFERENTIAL EXPRESSION ANALYSES
To get an overview of your quantified data with Principal Component Analysis (PCA), the variance between individual samples is displayed in two dimensions allowing for visual inspection of phenotype/ sample grouping as a function of RNA expression. (PCA is also effective for spotting outliers.)
The volcano-plot offers a visual representation of changes between samples compared and the significance of each individual change. In this way, the biggest, most significant changes in individual gene expressions can easily be identified, and the underlying values can be scrutinized in detail in the accompanying excel table.
LIST OF GENE EXPRESSION
A comprehensive list in excel of all genes, their differential expression and the degree of significance. This you can use as a catalogue to zoom in on a specific gene of interest.
Ex.: is the expression of receptorA changed in "treatment" compared to "control" and how much?