“Dots in Boxes" Visualization of qPCR Data

Learn how we analyzed plates and plates of qPCR data, and how Luna stacks up to the competition.

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Janine Borgaro, Ph.D.:

Over the course of developing the Luna qPCR portfolio, we've looked at lots and lots of qPCR curves.

 

We examined the Luna mixes, along with a variety of commercially-available mixes, on a broad set of targets, following manufacturer's recommendations.   By including a five-log dilutions of template and a no template control, all running in triplicate, 18 different qPCR curves were generated per target each target.  Each target was also run twice, by two different users. 

 

Because this data set became quite large, we needed to create a better, more scalable way to visualize our results. We started by plotting the calculated efficiency of the standard curve against the delta Cq. Which is the distance between the last template solution and the no template control, thereby translating the 18 wells worth of data per target into a single dot. By providing guidelines around the typically accepted values for these parameters, for example 90 to 110 percent efficiency, and a delta Cq of 3 or greater, this created a graphical visual we refer to as “dots in boxes”. 

 

However, it didn't quite capture all the relevant details of each run.

 

In order to represent additional information, the overall quality of the qPCR curves was scored on a scale from one to five. The scoring method was built upon previously published work by Hall et al, which encompassed factors such as curve sigmoidality and triplicate Cq tightness. The quality score was then used to define the size of the dot, where the larger dot represented a higher quality score.

 

This analysis method allowed us to quickly compare results across multiple targets or conditions and across a large data set, in order to better observe trends.  For example, here we see the data set that includes the Luna universal qPCR Master Mix, compared to a variety of other commercial mixes, designed for DNA dye-based qPCR, for example, SYBR, on a total of 18 unique genomic and cDNA targets, run in triplicate, by two different users.

 

Across these 36 experiments, we see the strong performance of the Luna Mix, where eighty-six percent of the experiments yielded high-quality results that fall in the box.

 

Similar results were observed for all Luna mixes, and these “dots in box” visuals can be found on each of the individual product pages. We’ve run thousands of qPCR experiments, and looked at curve after curve, to make the best possible qPCR reagents.

 

We hope the work that we did will enable the research you do.

 

For more information, visit LUNAqPCR.com

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