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

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 proce...

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Autores principales: Da Gama Duarte, Jessica, Goosen, Ryan W., Lawry, Peter J., Blackburn, Jonathan M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5828362/
https://www.ncbi.nlm.nih.gov/pubmed/29482592
http://dx.doi.org/10.1186/s13104-018-3266-0
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author Da Gama Duarte, Jessica
Goosen, Ryan W.
Lawry, Peter J.
Blackburn, Jonathan M.
author_facet Da Gama Duarte, Jessica
Goosen, Ryan W.
Lawry, Peter J.
Blackburn, Jonathan M.
author_sort Da Gama Duarte, Jessica
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13104-018-3266-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-58283622018-02-28 PMA: Protein Microarray Analyser, a user-friendly tool for data processing and normalization Da Gama Duarte, Jessica Goosen, Ryan W. Lawry, Peter J. Blackburn, Jonathan M. BMC Res Notes Research Note 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13104-018-3266-0) contains supplementary material, which is available to authorized users. BioMed Central 2018-02-27 /pmc/articles/PMC5828362/ /pubmed/29482592 http://dx.doi.org/10.1186/s13104-018-3266-0 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Note
Da Gama Duarte, Jessica
Goosen, Ryan W.
Lawry, Peter J.
Blackburn, Jonathan M.
PMA: Protein Microarray Analyser, a user-friendly tool for data processing and normalization
title PMA: Protein Microarray Analyser, a user-friendly tool for data processing and normalization
title_full PMA: Protein Microarray Analyser, a user-friendly tool for data processing and normalization
title_fullStr PMA: Protein Microarray Analyser, a user-friendly tool for data processing and normalization
title_full_unstemmed PMA: Protein Microarray Analyser, a user-friendly tool for data processing and normalization
title_short PMA: Protein Microarray Analyser, a user-friendly tool for data processing and normalization
title_sort pma: protein microarray analyser, a user-friendly tool for data processing and normalization
topic Research Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5828362/
https://www.ncbi.nlm.nih.gov/pubmed/29482592
http://dx.doi.org/10.1186/s13104-018-3266-0
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