Cargando…

ProteoSign v2: a faster and evolved user-friendly online tool for statistical analyses of differential proteomics

Bottom-up proteomics analyses have been proved over the last years to be a powerful tool in the characterization of the proteome and are crucial for understanding cellular and organism behaviour. Through differential proteomic analysis researchers can shed light on groups of proteins or individual p...

Descripción completa

Detalles Bibliográficos
Autores principales: Theodorakis, Evangelos, Antonakis, Andreas N, Baltsavia, Ismini, Pavlopoulos, Georgios A, Samiotaki, Martina, Amoutzias, Grigoris D, Theodosiou, Theodosios, Acuto, Oreste, Efstathiou, Georgios, Iliopoulos, Ioannis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262687/
https://www.ncbi.nlm.nih.gov/pubmed/33963869
http://dx.doi.org/10.1093/nar/gkab329
_version_ 1783719232050036736
author Theodorakis, Evangelos
Antonakis, Andreas N
Baltsavia, Ismini
Pavlopoulos, Georgios A
Samiotaki, Martina
Amoutzias, Grigoris D
Theodosiou, Theodosios
Acuto, Oreste
Efstathiou, Georgios
Iliopoulos, Ioannis
author_facet Theodorakis, Evangelos
Antonakis, Andreas N
Baltsavia, Ismini
Pavlopoulos, Georgios A
Samiotaki, Martina
Amoutzias, Grigoris D
Theodosiou, Theodosios
Acuto, Oreste
Efstathiou, Georgios
Iliopoulos, Ioannis
author_sort Theodorakis, Evangelos
collection PubMed
description Bottom-up proteomics analyses have been proved over the last years to be a powerful tool in the characterization of the proteome and are crucial for understanding cellular and organism behaviour. Through differential proteomic analysis researchers can shed light on groups of proteins or individual proteins that play key roles in certain, normal or pathological conditions. However, several tools for the analysis of such complex datasets are powerful, but hard-to-use with steep learning curves. In addition, some other tools are easy to use, but are weak in terms of analytical power. Previously, we have introduced ProteoSign, a powerful, yet user-friendly open-source online platform for protein differential expression/abundance analysis designed with the end-proteomics user in mind. Part of Proteosign's power stems from the utilization of the well-established Linear Models For Microarray Data (LIMMA) methodology. Here, we present a substantial upgrade of this computational resource, called ProteoSign v2, where we introduce major improvements, also based on user feedback. The new version offers more plot options, supports additional experimental designs, analyzes updated input datasets and performs a gene enrichment analysis of the differentially expressed proteins. We also introduce the deployment of the Docker technology and significantly increase the speed of a full analysis. ProteoSign v2 is available at http://bioinformatics.med.uoc.gr/ProteoSign.
format Online
Article
Text
id pubmed-8262687
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-82626872021-07-08 ProteoSign v2: a faster and evolved user-friendly online tool for statistical analyses of differential proteomics Theodorakis, Evangelos Antonakis, Andreas N Baltsavia, Ismini Pavlopoulos, Georgios A Samiotaki, Martina Amoutzias, Grigoris D Theodosiou, Theodosios Acuto, Oreste Efstathiou, Georgios Iliopoulos, Ioannis Nucleic Acids Res Web Server Issue Bottom-up proteomics analyses have been proved over the last years to be a powerful tool in the characterization of the proteome and are crucial for understanding cellular and organism behaviour. Through differential proteomic analysis researchers can shed light on groups of proteins or individual proteins that play key roles in certain, normal or pathological conditions. However, several tools for the analysis of such complex datasets are powerful, but hard-to-use with steep learning curves. In addition, some other tools are easy to use, but are weak in terms of analytical power. Previously, we have introduced ProteoSign, a powerful, yet user-friendly open-source online platform for protein differential expression/abundance analysis designed with the end-proteomics user in mind. Part of Proteosign's power stems from the utilization of the well-established Linear Models For Microarray Data (LIMMA) methodology. Here, we present a substantial upgrade of this computational resource, called ProteoSign v2, where we introduce major improvements, also based on user feedback. The new version offers more plot options, supports additional experimental designs, analyzes updated input datasets and performs a gene enrichment analysis of the differentially expressed proteins. We also introduce the deployment of the Docker technology and significantly increase the speed of a full analysis. ProteoSign v2 is available at http://bioinformatics.med.uoc.gr/ProteoSign. Oxford University Press 2021-05-08 /pmc/articles/PMC8262687/ /pubmed/33963869 http://dx.doi.org/10.1093/nar/gkab329 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Web Server Issue
Theodorakis, Evangelos
Antonakis, Andreas N
Baltsavia, Ismini
Pavlopoulos, Georgios A
Samiotaki, Martina
Amoutzias, Grigoris D
Theodosiou, Theodosios
Acuto, Oreste
Efstathiou, Georgios
Iliopoulos, Ioannis
ProteoSign v2: a faster and evolved user-friendly online tool for statistical analyses of differential proteomics
title ProteoSign v2: a faster and evolved user-friendly online tool for statistical analyses of differential proteomics
title_full ProteoSign v2: a faster and evolved user-friendly online tool for statistical analyses of differential proteomics
title_fullStr ProteoSign v2: a faster and evolved user-friendly online tool for statistical analyses of differential proteomics
title_full_unstemmed ProteoSign v2: a faster and evolved user-friendly online tool for statistical analyses of differential proteomics
title_short ProteoSign v2: a faster and evolved user-friendly online tool for statistical analyses of differential proteomics
title_sort proteosign v2: a faster and evolved user-friendly online tool for statistical analyses of differential proteomics
topic Web Server Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262687/
https://www.ncbi.nlm.nih.gov/pubmed/33963869
http://dx.doi.org/10.1093/nar/gkab329
work_keys_str_mv AT theodorakisevangelos proteosignv2afasterandevolveduserfriendlyonlinetoolforstatisticalanalysesofdifferentialproteomics
AT antonakisandreasn proteosignv2afasterandevolveduserfriendlyonlinetoolforstatisticalanalysesofdifferentialproteomics
AT baltsaviaismini proteosignv2afasterandevolveduserfriendlyonlinetoolforstatisticalanalysesofdifferentialproteomics
AT pavlopoulosgeorgiosa proteosignv2afasterandevolveduserfriendlyonlinetoolforstatisticalanalysesofdifferentialproteomics
AT samiotakimartina proteosignv2afasterandevolveduserfriendlyonlinetoolforstatisticalanalysesofdifferentialproteomics
AT amoutziasgrigorisd proteosignv2afasterandevolveduserfriendlyonlinetoolforstatisticalanalysesofdifferentialproteomics
AT theodosioutheodosios proteosignv2afasterandevolveduserfriendlyonlinetoolforstatisticalanalysesofdifferentialproteomics
AT acutooreste proteosignv2afasterandevolveduserfriendlyonlinetoolforstatisticalanalysesofdifferentialproteomics
AT efstathiougeorgios proteosignv2afasterandevolveduserfriendlyonlinetoolforstatisticalanalysesofdifferentialproteomics
AT iliopoulosioannis proteosignv2afasterandevolveduserfriendlyonlinetoolforstatisticalanalysesofdifferentialproteomics