- Course overview
- Search within this course
- Real-time PCR
- What is Next Generation DNA Sequencing?
- RNA sequencing
- Biological interpretation of gene expression data
- Genotyping, epigenetic and DNA/RNA-protein interaction methods
- DNA/RNA-protein interactions
- Quiz: Check your learning
- Your feedback
- Learn more
Differential expression analysis
The goal of differential expression analysis is to identify genes whose expression differs under different conditions. An important consideration for differential expression analysis is correction for multiple testing. This is a statistical phenomenon that occurs when thousands of comparisons (e.g. the comparison of expression of multiple genes in multiple conditions) are performed for a small number of samples (most microarray experiments have less than five biological replicates per condition). This leads to an increased chance of false positive results (4).
For Expression Atlas, the ‘limma’ package that is used to identify differentially expressed genes incorporates a method to correct for multiple testing. This method creates a log2 fold change ratio between the test and control condition and an ‘adjusted’ p-value that rates the significance of the difference (5).