PIIKA 2.5: Enhanced quality control of peptide microarrays for kinome analysis.

Peptide microarrays consisting of defined phosphorylation target sites are an effective approach for high throughput analysis of cellular kinase (kinome) activity. Kinome peptide arrays are highly customizable and do not require species-specific reagents to measure kinase activity, making them amena...

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Autores principales:	Connor Denomy, Conor Lazarou, Daniel Hogan, Antonio Facciuolo, Erin Scruten, Anthony Kusalik, Scott Napper
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/c9fd9544f95f4c37810fe36e38e13292
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spelling	oai:doaj.org-article:c9fd9544f95f4c37810fe36e38e132922021-12-02T20:14:41ZPIIKA 2.5: Enhanced quality control of peptide microarrays for kinome analysis.1932-620310.1371/journal.pone.0257232https://doaj.org/article/c9fd9544f95f4c37810fe36e38e132922021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0257232https://doaj.org/toc/1932-6203Peptide microarrays consisting of defined phosphorylation target sites are an effective approach for high throughput analysis of cellular kinase (kinome) activity. Kinome peptide arrays are highly customizable and do not require species-specific reagents to measure kinase activity, making them amenable for kinome analysis in any species. Our group developed software, Platform for Integrated, Intelligent Kinome Analysis (PIIKA), to enable more effective extraction of meaningful biological information from kinome peptide array data. A subsequent version, PIIKA2, unveiled new statistical tools and data visualization options. Here we introduce PIIKA 2.5 to provide two essential quality control metrics and a new background correction technique to increase the accuracy and consistency of kinome results. The first metric alerts users to improper spot size and informs them of the need to perform manual resizing to enhance the quality of the raw intensity data. The second metric uses inter-array comparisons to identify outlier arrays that sometimes emerge as a consequence of technical issues. In addition, a new background correction method, background scaling, can sharply reduce spatial biases within a single array in comparison to background subtraction alone. Collectively, the modifications of PIIKA 2.5 enable identification and correction of technical issues inherent to the technology and better facilitate the extraction of meaningful biological information. We show that these metrics demonstrably enhance kinome analysis by identifying low quality data and reducing batch effects, and ultimately improve clustering of treatment groups and enhance reproducibility. The web-based and stand-alone versions of PIIKA 2.5 are freely accessible at via http://saphire.usask.ca.Connor DenomyConor LazarouDaniel HoganAntonio FacciuoloErin ScrutenAnthony KusalikScott NapperPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 9, p e0257232 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Connor Denomy Conor Lazarou Daniel Hogan Antonio Facciuolo Erin Scruten Anthony Kusalik Scott Napper PIIKA 2.5: Enhanced quality control of peptide microarrays for kinome analysis.
description	Peptide microarrays consisting of defined phosphorylation target sites are an effective approach for high throughput analysis of cellular kinase (kinome) activity. Kinome peptide arrays are highly customizable and do not require species-specific reagents to measure kinase activity, making them amenable for kinome analysis in any species. Our group developed software, Platform for Integrated, Intelligent Kinome Analysis (PIIKA), to enable more effective extraction of meaningful biological information from kinome peptide array data. A subsequent version, PIIKA2, unveiled new statistical tools and data visualization options. Here we introduce PIIKA 2.5 to provide two essential quality control metrics and a new background correction technique to increase the accuracy and consistency of kinome results. The first metric alerts users to improper spot size and informs them of the need to perform manual resizing to enhance the quality of the raw intensity data. The second metric uses inter-array comparisons to identify outlier arrays that sometimes emerge as a consequence of technical issues. In addition, a new background correction method, background scaling, can sharply reduce spatial biases within a single array in comparison to background subtraction alone. Collectively, the modifications of PIIKA 2.5 enable identification and correction of technical issues inherent to the technology and better facilitate the extraction of meaningful biological information. We show that these metrics demonstrably enhance kinome analysis by identifying low quality data and reducing batch effects, and ultimately improve clustering of treatment groups and enhance reproducibility. The web-based and stand-alone versions of PIIKA 2.5 are freely accessible at via http://saphire.usask.ca.
format	article
author	Connor Denomy Conor Lazarou Daniel Hogan Antonio Facciuolo Erin Scruten Anthony Kusalik Scott Napper
author_facet	Connor Denomy Conor Lazarou Daniel Hogan Antonio Facciuolo Erin Scruten Anthony Kusalik Scott Napper
author_sort	Connor Denomy
title	PIIKA 2.5: Enhanced quality control of peptide microarrays for kinome analysis.
title_short	PIIKA 2.5: Enhanced quality control of peptide microarrays for kinome analysis.
title_full	PIIKA 2.5: Enhanced quality control of peptide microarrays for kinome analysis.
title_fullStr	PIIKA 2.5: Enhanced quality control of peptide microarrays for kinome analysis.
title_full_unstemmed	PIIKA 2.5: Enhanced quality control of peptide microarrays for kinome analysis.
title_sort	piika 2.5: enhanced quality control of peptide microarrays for kinome analysis.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/c9fd9544f95f4c37810fe36e38e13292
work_keys_str_mv	AT connordenomy piika25enhancedqualitycontrolofpeptidemicroarraysforkinomeanalysis AT conorlazarou piika25enhancedqualitycontrolofpeptidemicroarraysforkinomeanalysis AT danielhogan piika25enhancedqualitycontrolofpeptidemicroarraysforkinomeanalysis AT antoniofacciuolo piika25enhancedqualitycontrolofpeptidemicroarraysforkinomeanalysis AT erinscruten piika25enhancedqualitycontrolofpeptidemicroarraysforkinomeanalysis AT anthonykusalik piika25enhancedqualitycontrolofpeptidemicroarraysforkinomeanalysis AT scottnapper piika25enhancedqualitycontrolofpeptidemicroarraysforkinomeanalysis
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PIIKA 2.5: Enhanced quality control of peptide microarrays for kinome analysis.

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