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RPPanalyzer

A statistical tool developed to read reverse-phase protein array data, to perform the basic data analysis and to visualize the resulting biological information. The R-package provides different functions to compare protein expression levels of different samples and to normalize the data. Implemented plotting functions permit a quality control by monitoring data distribution and signal validity. Finally, the data can be visualized in heatmaps, boxplots, time course plots and correlation plots. RPPanalyzer is a flexible tool and tolerates a huge variety of different experimental designs.

NormaCurve

Allows to simultaneously quantify and normalize Reverse Phase Protein Arrays (RPPAs). NormaCurve is a normalization model that considers the two control arrays ctrl and sypro, as well as the two spatial effects Row and Column. The model, validated by cross-validation, allows the correction of spatial effects and corrects for differences in total amount of spotted proteins. It does not require a minimum amount of antibodies to be powerful and it is not affected by a bias in the chosen antibodies.

MIRACLE

A comprehensive and user-friendly web application bridging the gap between spotting and array analysis by conveniently keeping track of sample information. Data processing includes correction of staining bias, estimation of protein concentration from response curves, normalization for total protein amount per sample and statistical evaluation. Established analysis methods have been integrated with MIRACLE, offering experimental scientists an end-to-end solution for sample management and for carrying out data analysis. In addition, experienced users have the possibility to export data to R for more complex analyses.

RPPA Preprocess / Reverse Phase Protein Arrays Preprocess

A method for the determination and correction of systematic spatial variation in reverse phase protein arrays (RPPA) slides using positive control spots printed on each slide. RPPA Preprocess uses a simple bi-linear interpolation technique to obtain a surface representing the spatial variation occurring across the dimensions of a slide. This surface is used to calculate correction factors that can normalize the relative protein concentrations of the samples on each slide.