2D image analysis approaches have converged over the last ten years with every manufacturer providing a solution that offers a very similar workflow, developed to become as automated and accurate as it can be.

But speak to anyone using traditional 2D image analysis software and the overwhelming response is that it's far from ideal. This is because,

• The limitations of detection and matching require editing to correct the data. This is time consuming and adds subjectivity to your analysis
  
• Matching is difficult, even with "warping" features and any mis-matched spots create missing values in your 2D data, which reduces the statistical reliability of your results
  

Using traditional image analysis	Using Progenesis SameSpots

SameSpots gives 100% matching with no missing values in your data

A major problem following traditional analysis approaches, including 2D DIGE, is that they introduce missing values into the data. 2D gel analysis as a technique introduces a high amount of variation on top of the biological variation that already exists in an experiment. To counter this you need to run high numbers of replicates, something that traditional 2D analysis approaches do not easily support.

 

Typical levels of missing values introduced with increasing numbers of replicates/experiment using traditional analysis approach
No. Gels	No. Spots detected	No. Matched in all gels	% Missing Values
2	1000	900	10
5	1000	750	25
10	1000	600	40
20	1000	400	60
100	1000	<100	>90%

Another big problem exists when you run more replicates with traditional 2D analysis. The more gels you run the more you increase the number of missing values in your experiment. This is because the software struggles to match every spot in every image as the number of gels increases.

What this means is that you spend time carefully generating samples, doing the wet work and running the gels, while all the time losing potentially interesting proteins. Then as our figures show, you can lose even more data during the image analysis step! With SameSpots you get 100% matching and no missing values with any number of replicates.