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Combined Correctness Can Enrich Proteomics

New Metrics Improve Potential in 2-D Gels
  • Ola Forsstrom-Olsson
  • ,
  • Anna Kapferer




False Positives





False Negatives




The Combined Correctness Principle





Measuring Combined Correctness




It should be mentioned that the number of ambiguously categorized spots or matches is usually low, which leads to a negligible effect on the overall correctness measurements. Using the estimated spot detection correctness and the matching correctness, the combined correctness of any 2-D gel-image analysis can be calculated using the following formula:

Combined Correctness = Spot Detection Correctness x Pair Matching Correctness

According to our hypothesis, the value for combined correctness should be inversely proportional to the number of false positives and false negatives in the image analysis and thus indicative of the overall data quality. And indeed, when the ratio of false positives and false negatives in an analysis is estimated and plotted against the combined correctness, we see exactly this correlation. As the combined correctness is increased, both the ratio of false positives and false negatives decreases (data will be published this year).

So far, this has been the case every time, without exception. Combined correctness is simply a way of putting a measurement on this seemingly evident relation.

Consequences for 2-D Gel-Based Proteomics

The introduction of metrics such as combined correctness can have a tremendous impact on 2-D gel-based proteomics. Missing on average 75% of the interesting differences is a sign that the current approaches and procedures are far from optimal. By rigorously implementing correctness measurements and quality checkpoints at each step of the image analysis, it is possible to dramatically increase the discovery potential in 2-D gel-based experiments.

The key point here must be the application of standardized metrics that allow the systematic and unbiased optimization of spot detection and matching. Research at Ludesi shows that it is possible to routinely integrate such metrics into the 2-D gel image-analysis workflow, and thereby, scientists may start tapping into the true potential of 2-D gel electrophoresis.


Ola Forsstrom-Olsson is CEO and founder, and Anna Kapferer is an application specialist at Ludesi. Web: E-mail: