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PTMphinder: an R package for PTM site localization and motif extraction from proteomic datasets

BACKGROUND: Mass-spectrometry-based proteomics is a prominent field of study that allows for the unbiased quantification of thousands of proteins from a particular sample. A key advantage of these techniques is the ability to detect protein post-translational modifications (PTMs) and localize them t...

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Autores principales: Wozniak, Jacob M., Gonzalez, David J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6555389/
https://www.ncbi.nlm.nih.gov/pubmed/31198645
http://dx.doi.org/10.7717/peerj.7046
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author Wozniak, Jacob M.
Gonzalez, David J.
author_facet Wozniak, Jacob M.
Gonzalez, David J.
author_sort Wozniak, Jacob M.
collection PubMed
description BACKGROUND: Mass-spectrometry-based proteomics is a prominent field of study that allows for the unbiased quantification of thousands of proteins from a particular sample. A key advantage of these techniques is the ability to detect protein post-translational modifications (PTMs) and localize them to specific amino acid residues. These approaches have led to many significant findings in a wide range of biological disciplines, from developmental biology to cancer and infectious diseases. However, there is a current lack of tools available to connect raw PTM site information to biologically meaningful results in a high-throughput manner. Furthermore, many of the available tools require significant programming knowledge to implement. RESULTS: The R package PTMphinder was designed to enable researchers, particularly those with minimal programming background, to thoroughly analyze PTMs in proteomic data sets. The package contains three functions: parseDB, phindPTMs and extractBackground. Together, these functions allow users to reformat proteome databases for easier analysis, localize PTMs within full proteins, extract motifs surrounding the identified sites and create proteome-specific motif backgrounds for statistical purposes. Beta-testing of this R package has demonstrated its simplicity and ease of integration with existing tools. CONCLUSION: PTMphinder empowers researchers to fully analyze and interpret PTMs derived from proteomic data. This package is simple enough for researchers with limited programming experience to understand and implement. The data produced from this package can inform subsequent research by itself and also be used in conjunction with other tools, such as motif-x, for further analysis.
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spelling pubmed-65553892019-06-13 PTMphinder: an R package for PTM site localization and motif extraction from proteomic datasets Wozniak, Jacob M. Gonzalez, David J. PeerJ Biochemistry BACKGROUND: Mass-spectrometry-based proteomics is a prominent field of study that allows for the unbiased quantification of thousands of proteins from a particular sample. A key advantage of these techniques is the ability to detect protein post-translational modifications (PTMs) and localize them to specific amino acid residues. These approaches have led to many significant findings in a wide range of biological disciplines, from developmental biology to cancer and infectious diseases. However, there is a current lack of tools available to connect raw PTM site information to biologically meaningful results in a high-throughput manner. Furthermore, many of the available tools require significant programming knowledge to implement. RESULTS: The R package PTMphinder was designed to enable researchers, particularly those with minimal programming background, to thoroughly analyze PTMs in proteomic data sets. The package contains three functions: parseDB, phindPTMs and extractBackground. Together, these functions allow users to reformat proteome databases for easier analysis, localize PTMs within full proteins, extract motifs surrounding the identified sites and create proteome-specific motif backgrounds for statistical purposes. Beta-testing of this R package has demonstrated its simplicity and ease of integration with existing tools. CONCLUSION: PTMphinder empowers researchers to fully analyze and interpret PTMs derived from proteomic data. This package is simple enough for researchers with limited programming experience to understand and implement. The data produced from this package can inform subsequent research by itself and also be used in conjunction with other tools, such as motif-x, for further analysis. PeerJ Inc. 2019-06-04 /pmc/articles/PMC6555389/ /pubmed/31198645 http://dx.doi.org/10.7717/peerj.7046 Text en ©2019 Wozniak and Gonzalez http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Biochemistry
Wozniak, Jacob M.
Gonzalez, David J.
PTMphinder: an R package for PTM site localization and motif extraction from proteomic datasets
title PTMphinder: an R package for PTM site localization and motif extraction from proteomic datasets
title_full PTMphinder: an R package for PTM site localization and motif extraction from proteomic datasets
title_fullStr PTMphinder: an R package for PTM site localization and motif extraction from proteomic datasets
title_full_unstemmed PTMphinder: an R package for PTM site localization and motif extraction from proteomic datasets
title_short PTMphinder: an R package for PTM site localization and motif extraction from proteomic datasets
title_sort ptmphinder: an r package for ptm site localization and motif extraction from proteomic datasets
topic Biochemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6555389/
https://www.ncbi.nlm.nih.gov/pubmed/31198645
http://dx.doi.org/10.7717/peerj.7046
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