Protocol for the processing and downstream analysis of phosphoproteomic data with PhosR

Hani Jieun Kim; Taiyun Kim; Di Xiao; Pengyi Yang

STAR Protocols (Jun 2021)

Protocol for the processing and downstream analysis of phosphoproteomic data with PhosR

Hani Jieun Kim,
Taiyun Kim,
Di Xiao,
Pengyi Yang

Affiliations

Hani Jieun Kim: Charles Perkins Centre, School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia; Computational Systems Biology Group, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia; Corresponding author
Taiyun Kim: Charles Perkins Centre, School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia; Computational Systems Biology Group, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
Di Xiao: Computational Systems Biology Group, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
Pengyi Yang: Charles Perkins Centre, School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia; Computational Systems Biology Group, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia; Corresponding author

Journal volume & issue: Vol. 2, no. 2
p. 100585

Abstract

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Summary: Analysis of phosphoproteomic data requires advanced computational methodologies. To this end, we developed PhosR, a set of tools and methodologies implemented in R to allow the comprehensive analysis of phosphoproteomic data. PhosR enables processing steps such as imputation, normalization, and functional analysis such as kinase activity inference and signalome construction. Together, PhosR facilitates interpretation and discovery from large-scale phosphoproteomic data sets.For complete details on the use and execution of this protocol, please refer to Kim et al. (2021).

Published in STAR Protocols

ISSN: 2666-1667 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Science: Science (General)
Website: https://star-protocols.cell.com/

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