Principle
RNA-Seq profiles the transcriptome of cells or tissues to compare expression between study groups. Suitable designs also support transcript structure and alternative splicing analysis, providing expression-level evidence for complementary omics studies.
Applications
- Compare expression profiles across cells, tissues or treatments
- Identify differentially expressed genes and functional pathways
- Investigate transcriptional changes during development, differentiation or disease
Method features
- Provides sequence and expression abundance information
- Analysis is tailored to the organism and research question
- Suitable coverage supports investigation of low-abundance transcripts
Workflow
- 01
Assess samples and RNA quality
- 02
Select an RNA enrichment strategy and prepare libraries
- 03
Sequence and check raw data quality
- 04
Quantify expression and interpret differential and functional results
This is a workflow overview. Experimental and analytical details depend on sample conditions and research objectives.