PAWER: protein array web exploreR

Abstract

Background: Protein microarray is a well-established approach for characterizing activity levels of thousands of proteins in a parallel manner. Analysis of protein microarray data is complex and time-consuming, while existing solutions are either outdated or challenging to use without programming skills. The typical data analysis pipeline consists of a data preprocessing step, followed by differential expression analysis, which is then put into context via functional enrichment. Normally, biologists would need to assemble their own workflow by combining a set of unrelated tools to analyze experimental data. Provided that most of these tools are developed independently by various bioinformatics groups, making them work together could be a real challenge.

Results: Here we present PAWER, the online web tool dedicated solely to protein microarray analysis. PAWER enables biologists to carry out all the necessary analysis steps in one go. PAWER provides access to state-of-the-art computational methods through the user-friendly interface, resulting in publication-ready illustrations. We also provide an R package for more advanced use cases, such as bespoke analysis workflows.

Conclusions: PAWER is freely available at https://biit.cs.ut.ee/pawer .

Keywords: Data analysis; Normalisation; Protein microarray; Visualisation; Web tool.

Fig. 1

PAWER pipeline. Raw GPR files are uploaded to PAWER (1), then the system proceeds to identifying foreground and background intensities and a panel of control proteins that can be used for normalisation (2). Robust linear model is then used to estimate and remove the technical artifacts associated with each array and array block (3). Normalised data is then combined with sample metadata (4) to produce a list of differentially expressed proteins (5). PAWER is linked with two other tools (g:Profiler and ClustVis) to enable additional analysis, namely: protein enrichment analysis. The figure was generated in Keynote, version 10.1 (6913)