Analysis of protein array data

Miao Sun, The University of Texas School of Public Health

Abstract

Protein microarray has been widely used in the biological and biomedical fields. There are two categories in protein microarrays: forward phase protein arrays (FPPA) and reverse phase protein arrays (RPPA). With its own advantages, RPPA has been successfully applied in detecting protein signal pathway, analysis of protein profiling and so on. The most popular analytic methods in RPPA data analysis are SuperCurve method and Serial Dilution Curve method. Both of these methods require estimation of the background noise fluorescence. However, this estimation is usually not accurate based on the sample bias and spatial bias. Here, we propose new methods to overcome this inaccuracy. Briefly, for each two consecutive RPPA cycles, we subtract the later cycle from the former cycle, transforming the n cycle data into n-1 cycle data. Therefore, the data in the n-1 cycle is supposed to be removed most of the background florescence noise. We then use the n-1 cycle data to fit the SuperCurve model and the Serial Dilution Curve model. We proposed two modified SuperCurve methods and one modified Serial Dilution Curve method. To evaluate our proposed methods, we compared the accuracy and precision between our proposed models and the original models by testing both practical and simulated datasets. For practical dataset, we found that our modified SuperCurve methods and modified Serial Dilution Curve method had more precise results. For simulated dataset, we tested our methods both under small background noise and large background noise. Our modified SuperCurve method 2 performed best under both background noises. Our modified Serial Dilution Curve showed more accurate under both background noises but the original method showed more precise in our simulated dataset analysis. Overall, the differencing method is supposed to avoid most of the unknown background noise, so it is theoretically more accurate and precise. Our modified methods are easy to perform and are recommended to apply to all current RPPA data analysis.

Subject Area

Biostatistics

Recommended Citation

Sun, Miao, "Analysis of protein array data" (2014). Texas Medical Center Dissertations (via ProQuest). AAI1566370.
https://digitalcommons.library.tmc.edu/dissertations/AAI1566370

Share

COinS