PhosR enables processing and functional analysis of phosphoproteomic data
Summary: Mass spectrometry (MS)-based phosphoproteomics has revolutionized our ability to profile phosphorylation-based signaling in cells and tissues on a global scale. To infer the action of kinases and signaling pathways in phosphoproteomic experiments, we present PhosR, a set of tools and method...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-02-01
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| Series: | Cell Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S221112472100084X |
| _version_ | 1828969956125966336 |
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| author | Hani Jieun Kim Taiyun Kim Nolan J. Hoffman Di Xiao David E. James Sean J. Humphrey Pengyi Yang |
| author_facet | Hani Jieun Kim Taiyun Kim Nolan J. Hoffman Di Xiao David E. James Sean J. Humphrey Pengyi Yang |
| author_sort | Hani Jieun Kim |
| collection | DOAJ |
| description | Summary: Mass spectrometry (MS)-based phosphoproteomics has revolutionized our ability to profile phosphorylation-based signaling in cells and tissues on a global scale. To infer the action of kinases and signaling pathways in phosphoproteomic experiments, we present PhosR, a set of tools and methodologies implemented in a suite of R packages facilitating comprehensive analysis of phosphoproteomic data. By applying PhosR to both published and new phosphoproteomic datasets, we demonstrate capabilities in data imputation and normalization by using a set of “stably phosphorylated sites” and in functional analysis for inferring active kinases and signaling pathways. In particular, we introduce a “signalome” construction method for identifying a collection of signaling modules to summarize and visualize the interaction of kinases and their collective actions on signal transduction. Together, our data and findings demonstrate the utility of PhosR in processing and generating biological knowledge from MS-based phosphoproteomic data. |
| first_indexed | 2024-12-14T12:41:13Z |
| format | Article |
| id | doaj.art-6d20131845ba4856a2d27bc5294dac18 |
| institution | Directory Open Access Journal |
| issn | 2211-1247 |
| language | English |
| last_indexed | 2024-12-14T12:41:13Z |
| publishDate | 2021-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Cell Reports |
| spelling | doaj.art-6d20131845ba4856a2d27bc5294dac182022-12-21T23:00:54ZengElsevierCell Reports2211-12472021-02-01348108771PhosR enables processing and functional analysis of phosphoproteomic dataHani Jieun Kim0Taiyun Kim1Nolan J. Hoffman2Di Xiao3David E. James4Sean J. Humphrey5Pengyi Yang6School 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; Charles Perkins Centre, The University of Sydney, Sydney, NSW, AustraliaSchool 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; Charles Perkins Centre, The University of Sydney, Sydney, NSW, AustraliaCharles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; School of Environmental and Life Sciences, The University of Sydney, Sydney, NSW, AustraliaComputational Systems Biology Group, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, AustraliaCharles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; School of Environmental and Life Sciences, The University of Sydney, Sydney, NSW, Australia; Sydney Medical School, The University of Sydney, Sydney, NSW, AustraliaCharles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; School of Environmental and Life Sciences, The University of Sydney, Sydney, NSW, AustraliaSchool 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; Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; Corresponding authorSummary: Mass spectrometry (MS)-based phosphoproteomics has revolutionized our ability to profile phosphorylation-based signaling in cells and tissues on a global scale. To infer the action of kinases and signaling pathways in phosphoproteomic experiments, we present PhosR, a set of tools and methodologies implemented in a suite of R packages facilitating comprehensive analysis of phosphoproteomic data. By applying PhosR to both published and new phosphoproteomic datasets, we demonstrate capabilities in data imputation and normalization by using a set of “stably phosphorylated sites” and in functional analysis for inferring active kinases and signaling pathways. In particular, we introduce a “signalome” construction method for identifying a collection of signaling modules to summarize and visualize the interaction of kinases and their collective actions on signal transduction. Together, our data and findings demonstrate the utility of PhosR in processing and generating biological knowledge from MS-based phosphoproteomic data.http://www.sciencedirect.com/science/article/pii/S221112472100084Xphosphoproteomicssignalling networksimputationnormalisationbatch correctionstably phosphorylated sites |
| spellingShingle | Hani Jieun Kim Taiyun Kim Nolan J. Hoffman Di Xiao David E. James Sean J. Humphrey Pengyi Yang PhosR enables processing and functional analysis of phosphoproteomic data Cell Reports phosphoproteomics signalling networks imputation normalisation batch correction stably phosphorylated sites |
| title | PhosR enables processing and functional analysis of phosphoproteomic data |
| title_full | PhosR enables processing and functional analysis of phosphoproteomic data |
| title_fullStr | PhosR enables processing and functional analysis of phosphoproteomic data |
| title_full_unstemmed | PhosR enables processing and functional analysis of phosphoproteomic data |
| title_short | PhosR enables processing and functional analysis of phosphoproteomic data |
| title_sort | phosr enables processing and functional analysis of phosphoproteomic data |
| topic | phosphoproteomics signalling networks imputation normalisation batch correction stably phosphorylated sites |
| url | http://www.sciencedirect.com/science/article/pii/S221112472100084X |
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