Quantitative Analysis

Delta2D uses advanced image segmentation algorithms to detect protein spots. Gel image files in all major file formats are supported, taking into account vendor specific calibration information.

Delta2D's 100% spot matching produces complete expression profiles for every protein. Besides higher throughput, this leads to significantly improved statistical confidence, so you can, for example, identify more biomarker candidates from the same experiment. Other approaches to spot detection and matching lead to inconsistencies like missing values in expression profiles, and ambiguities in the profiles themselves. Delta2D's 100% spot matching is based on advanced image processing methods. It was introduced in 2003.

Delta2D displays quantitative data in flexible, easy to use tabular views that support your analysis strategy. Table rows can be filtered and sorted, making it easy to find or highlight spots with a given expression ratio, or those that have not yet been labeled, for example. You can mark or hide spots based on combined criteria, such as: “hide all spots whose expression levels changed by less than a factor of two and whose quantity is smaller than 0.1”. Delta2D's unique histogram-based filters let you go beyond simple cutoff criteria and fixed absolute thresholds. Define criteria that are consistent across the whole analysis project, such as: "Highlight the weakest 10% of all spots", or "Hide all except the strongest spots that account for 85% of the total quantity".

A variety of charts is available for visualizing expression profiles: scatter plots for comparison between two images, and various bar charts for displaying expression profiles across the whole experiment. Spot selection and visibility is fully synchronized between the gel views, the quantitation tables, scatter plots, and expression profiles, so you can go from image to data and back again with ease.

In the statistics table you can see the maximum, minimum, or mean intensity of a spot within a replicate group. By filtering on relative standard deviations you can identify spots that are not well reproduced in the replicate series. Use Student t-Test scores to filter for spots with significantly changed expression levels.

One click in the quantitation table will open a comprehensive, interactive report in Excel, including spot intensity histograms, scatterplots, and statistics. Of course, you can also export the complete raw analysis data to Excel and other applications for further processing.

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