Gene Expression Data Quality is Shaped Before Analysis

Explore the hidden pitfalls that could be derailing your gene expression analysis in this whitepaper outlining the key challenges you’ll come across.

From sample collection and stabilization to RNA extraction and quality control, each step affects which RNA species are preserved and how accurately they are represented in downstream NGS, qPCR, or dPCR analyses.

You’ll learn:

• The “sample-to-signal” principle: how upstream RNA handling shapes downstream data
• The practical trade-offs between poly(A) selection and rRNA depletion, and why a high RIN does not guarantee meaningful data
• How RNA-seq and PCR differ in tolerance to degradation, and what this means for your sample type