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. 2018 Feb 27;11(1):156.
doi: 10.1186/s13104-018-3266-0.

PMA: Protein Microarray Analyser, a user-friendly tool for data processing and normalization

Jessica Da Gama Duarte  1   2 , Ryan W Goosen  3 , Peter J Lawry  4 , Jonathan M Blackburn  3   5
Affiliations

PMA: Protein Microarray Analyser, a user-friendly tool for data processing and normalization

Jessica Da Gama Duarte et al. BMC Res Notes. .

Abstract

Objective: Protein microarrays provide a high-throughput platform to measure protein interactions and associated functions, and can aid in the discovery of cancer biomarkers. The resulting protein microarray data can however be subject to systematic bias and noise, thus requiring a robust data processing, normalization and analysis pipeline to ensure high quality and robust results. To date, a comprehensive data processing pipeline is yet to be developed. Furthermore, a lack of analysis consistency is evident amongst different research groups, thereby impeding collaborative data consolidation and comparison. Thus, we sought to develop an accessible data processing tool using methods that are generalizable to the protein microarray field and which can be adapted to individual array layouts with minimal software engineering expertise.

Results: We developed an improved version of a previously developed pipeline of protein microarray data processing and implemented it as an open source software tool, with particular focus on widening its use and applicability. The Protein Microarray Analyser software presented here includes the following tools: (1) neighbourhood background correction, (2) net intensity correction, (3) user-defined noise threshold, (4) user-defined CV threshold amongst replicates and (5) assay controls, (6) composite 'pin-to-pin' normalization amongst sub-arrays, and (7) 'array-to-array' normalization amongst whole arrays.

Keywords: PMA; Protein Microarray Analyser; Protein microarrays.

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Figures

Fig. 1
Fig. 1
Schematic of the Protein Microarray Analyser data processing and normalization pipeline. Extracted raw data is corrected and filtered to remove or flag problematic data and obtain high quality results that can then be used across a multitude of appropriate data analysis tools
Fig. 2
Fig. 2
Protein Microarray Analyser software interface. This user-friendly interface allows the user to select raw data files, select default or custom settings, and lists the methods to be run on the dataset
See this image and copyright information in PMC

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