Have you ever compared two qPCR plates and wondered why your results suddenly made no sense?

Even when your pipetting was perfect, small shifts in amplification curves, inconsistent controls and confusing Ct values can wreck your conclusions. This isn’t necessarily user error. It's a classic example of the importance of multiplate analysis.

In high-throughput labs, it is almost impossible to remain within the confines of a single 96- or 384-well plate. However, comparing results from different plates is not always straightforward.

Why is it so difficult?

Even when every plate runs smoothly, subtle differences in:

• temperature uniformity
• reagent performance
• pipetting accuracy
• threshold settings
  

...can result in significant variation, enough to throw off comparative Ct values, melt curve interpretation, or quantification.

If you’re comparing expression levels between plates without the right controls or software support, you're at risk of drawing the wrong conclusions. This is where multiplate analysis becomes crucial.

So… what is multiplate analysis?

Multiplate analysis enables you to compare and normalize qPCR data from different plates or runs. Rather than analyzing each plate as a separate experiment, you can combine your data in a consistent and statistically sound way.

Why does it matter?

• Eliminates inter-plate variation (even small shifts in pipetting or detection matter!)
• Improves confidence in results, especially when working with biological replicates
• Simplifies complex experimental designs, like time courses or multiple conditions

Real-life example?

Imagine you are profiling 20 samples for five genes over several days. You’ll need several plates. However, if you don't normalize correctly across those plates, any conclusions you draw about differences in gene expression might be incorrect.

Best practices for Multiplate qPCR Analysis

• Include interplate calibrators: use a reference sample on every plate to help correct for technical differences between runs.
• Use consistent reference genes: the behaviour of your housekeeping gene needs to be reliable across all plates. Always validate it before starting your analysis.
• Standardize everything: the same pipettes. Same reagent batch. Same qPCR machine. Same run settings. (Yes, it makes a difference.)
• Document plate layout: especially when working with many targets or replicates.
• Don’t eyeball it: Use software that supports multiplate analysis and applies consistent normalization methods.

Coming soon: FastGene qFYR Plus with smarter software