Kinomics toolbox—A web platform for analysis and viewing of kinomic peptide array data

Dussaq, Alex M.; Kennell, Timothy; Eustace, Nicholas; Anderson, Joshua C.; Almeida, Jonas S.; Willey, Christopher D.

doi:10.1371/journal.pone.0202139

Cited by 14 publications

(9 citation statements)

References 28 publications

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“…The extracted data can be directly used for downstream analysis. Other tools are also developed allowing downstream analysis of PamChip data, such as the Kinomics toolbox 11 , indicating the interest for this technology and the need for analysis frameworks. The aim of providing this software as an open-source GPL license is to help researchers take full advantage of the technology and also integrate it more in their complex data acquisition environment.…”

Section: Resultsmentioning

confidence: 99%

PamgeneAnalyzeR open and reproducible pipeline for kinase profiling

Bekkar

Nasrallah

Guex

et al. 2019

Preprint

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Protein phosphorylation - catalyzed by protein kinases - is the most common post-translational modification. It increases the functional diversity of the proteome and influences various aspects of normal physiology and can be altered in disease states. High throughput profiling of kinases is becoming an essential experimental approach to investigate their activity and this can be achieved using technologies such as PamChip® arrays provided by PamGene for kinase activity measurement. Here we present “pamgeneAnalyzeR”, an R package developed as an alternative to the manual steps necessary to extract the data from PamChip® peptide microarrays images in a reproducible and robust manner. The extracted data can be directly used for downstream analysis.Availability and implementationPamgeneAnalyzeR is implemented in R and can be obtained from https://github.com/amelbek/pamgeneAnalyzeR.

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Section: Resultsmentioning

confidence: 99%

PamgeneAnalyzeR open and reproducible pipeline for kinase profiling

Bekkar

Nasrallah

Guex

et al. 2019

Preprint

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“…While many laboratories have successfully used end-level readings to identify biologically relevant targets, this being the method that KRSA currently uses, Dussaq et al notes that the kinetic data is under-utilized and has the potential to uncover additional relevant information. This is mainly applicable to the tyrosine kinase chip, but not the serine-threonine kinase chip used for this study (Dussaq et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

“…Bioinformatics tools that are specifically designed to analyze kinome array datasets are beginning to emerge. One of these analytic tools is the Kinomics Toolkit, which gives users a platform for exploration of the peptide phosphorylation data, but does not provide upstream kinase predictions (Dussaq et al, 2018). This application pre-processes data, serves as a public data repository, and provides developers the opportunity to engage with the data in an SDK (software development kit).…”

Section: Introductionmentioning

confidence: 99%

KRSA: Network-based Prediction of Differential Kinase Activity from Kinome Array Data

DePasquale

Alganem

Bentea

et al. 2020

Preprint

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MotivationPhosphorylation by serine-threonine and tyrosine kinases is critical for determining protein function. Array-based approaches for measuring multiple kinases allow for the testing of differential phosphorylation between conditions for distinct sub-kinomes. While bioinformatics tools exist for processing and analyzing such kinome array data, current open-source tools lack the automated approach of upstream kinase prediction and network modeling. The presented tool, alongside other tools and methods designed for gene expression and protein-protein interaction network analyses, help the user better understand the complex regulation of gene and protein activities that forms biological systems and cellular signaling networks.ResultsWe present the Kinome Random Sampling Analyzer (KRSA), a web-application for kinome array analysis. While the underlying algorithm has been experimentally validated in previous publications, we tested the full KRSA application on dorsolateral prefrontal cortex (DLPFC) in male (n=3) and female (n=3) subjects to identify differential phosphorylation and upstream kinase activity. Kinase activity differences between males and females were compared to a previously published kinome dataset (11 female and 7 male subjects) which showed similar patterns to the global phosphorylation signal. Additionally, kinase hits were compared to gene expression databases for in silico validation at the transcript level and showed differential gene expression of kinases.Availability and implementationKRSA as a web-based application can be found at http://bpg-n.utoledo.edu:3838/CDRL/KRSA/. The code and data are available at https://github.com/kalganem/KRSA.Supplementary informationSupplementary data are available online.

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“…The extracted data can be directly used for downstream analysis. Other tools are also developed allowing downstream analysis of PamChip data, such as the Kinomics toolbox ( Dussaq et al , 2018 ), indicating the interest for this technology and the need for analysis frameworks. The aim of providing this software as an open-source GPL license is to help researchers take full advantage of the technology and also integrate it more in their complex dataacquisition environment.…”

Section: Discussionmentioning

confidence: 99%

PamgeneAnalyzeR: open and reproducible pipeline for kinase profiling

et al. 2020

View full text Add to dashboard Cite

Protein phosphorylation – catalyzed by protein kinases - is the most common post-translational modification. It increases the functional diversity of the proteome and influences various aspects of normal physiology and can be altered in disease states. High throughput profiling of kinases is becoming an essential experimental approach to investigate their activity and this can be achieved using technologies such as PamChip® arrays provided by PamGene for kinase activity measurement. Here we present “pamgeneAnalyzeR”, an R package developed as an alternative to the manual steps necessary to extract the data from PamChip® peptide microarrays images in a reproducible and robust manner. The extracted data can be directly used for downstream analysis. Availability and implementation PamgeneAnalyzeR is implemented in R and can be obtained from https://github.com/amelbek/pamgeneAnalyzeR.

show abstract

Kinomics toolbox—A web platform for analysis and viewing of kinomic peptide array data

Cited by 14 publications

References 28 publications

PamgeneAnalyzeR open and reproducible pipeline for kinase profiling

PamgeneAnalyzeR open and reproducible pipeline for kinase profiling

KRSA: Network-based Prediction of Differential Kinase Activity from Kinome Array Data

PamgeneAnalyzeR: open and reproducible pipeline for kinase profiling

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