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DEP2: an upgraded comprehensive analysis toolkit for quantitative proteomics data

SUMMARY: Mass spectrometry (MS)-based proteomics has become the most powerful approach to study the proteome of given biological and clinical samples. Advancements in sample preparation and MS detection have extended the application of proteomics but have also brought new demands on data analysis. A...

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Autores principales: Feng, Zhenhuan, Fang, Peiyang, Zheng, Hui, Zhang, Xiaofei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10466079/
https://www.ncbi.nlm.nih.gov/pubmed/37624922
http://dx.doi.org/10.1093/bioinformatics/btad526
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author Feng, Zhenhuan
Fang, Peiyang
Zheng, Hui
Zhang, Xiaofei
author_facet Feng, Zhenhuan
Fang, Peiyang
Zheng, Hui
Zhang, Xiaofei
author_sort Feng, Zhenhuan
collection PubMed
description SUMMARY: Mass spectrometry (MS)-based proteomics has become the most powerful approach to study the proteome of given biological and clinical samples. Advancements in sample preparation and MS detection have extended the application of proteomics but have also brought new demands on data analysis. Appropriate proteomics data analysis workflow mainly requires quality control, hypothesis testing, functional mining, and visualization. Although there are numerous tools for each process, an efficient and universal tandem analysis toolkit to obtain a quick overall view of various proteomics data is still urgently needed. Here, we present DEP2, an updated version of DEP we previously established, for proteomics data analysis. We amended the analysis workflow by incorporating alternative approaches to accommodate diverse proteomics data, introducing peptide-protein summarization and coupling biological function exploration. In summary, DEP2 is a well-rounded toolkit designed for protein- and peptide-level quantitative proteomics data. It features a more flexible differential analysis workflow and includes a user-friendly Shiny application to facilitate data analysis. AVAILABILITY AND IMPLEMENTATION: DEP2 is available at https://github.com/mildpiggy/DEP2, released under the MIT license. For further information and usage details, please refer to the package website at https://mildpiggy.github.io/DEP2/.
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spelling pubmed-104660792023-08-31 DEP2: an upgraded comprehensive analysis toolkit for quantitative proteomics data Feng, Zhenhuan Fang, Peiyang Zheng, Hui Zhang, Xiaofei Bioinformatics Applications Note SUMMARY: Mass spectrometry (MS)-based proteomics has become the most powerful approach to study the proteome of given biological and clinical samples. Advancements in sample preparation and MS detection have extended the application of proteomics but have also brought new demands on data analysis. Appropriate proteomics data analysis workflow mainly requires quality control, hypothesis testing, functional mining, and visualization. Although there are numerous tools for each process, an efficient and universal tandem analysis toolkit to obtain a quick overall view of various proteomics data is still urgently needed. Here, we present DEP2, an updated version of DEP we previously established, for proteomics data analysis. We amended the analysis workflow by incorporating alternative approaches to accommodate diverse proteomics data, introducing peptide-protein summarization and coupling biological function exploration. In summary, DEP2 is a well-rounded toolkit designed for protein- and peptide-level quantitative proteomics data. It features a more flexible differential analysis workflow and includes a user-friendly Shiny application to facilitate data analysis. AVAILABILITY AND IMPLEMENTATION: DEP2 is available at https://github.com/mildpiggy/DEP2, released under the MIT license. For further information and usage details, please refer to the package website at https://mildpiggy.github.io/DEP2/. Oxford University Press 2023-08-25 /pmc/articles/PMC10466079/ /pubmed/37624922 http://dx.doi.org/10.1093/bioinformatics/btad526 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Feng, Zhenhuan
Fang, Peiyang
Zheng, Hui
Zhang, Xiaofei
DEP2: an upgraded comprehensive analysis toolkit for quantitative proteomics data
title DEP2: an upgraded comprehensive analysis toolkit for quantitative proteomics data
title_full DEP2: an upgraded comprehensive analysis toolkit for quantitative proteomics data
title_fullStr DEP2: an upgraded comprehensive analysis toolkit for quantitative proteomics data
title_full_unstemmed DEP2: an upgraded comprehensive analysis toolkit for quantitative proteomics data
title_short DEP2: an upgraded comprehensive analysis toolkit for quantitative proteomics data
title_sort dep2: an upgraded comprehensive analysis toolkit for quantitative proteomics data
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10466079/
https://www.ncbi.nlm.nih.gov/pubmed/37624922
http://dx.doi.org/10.1093/bioinformatics/btad526
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AT zhangxiaofei dep2anupgradedcomprehensiveanalysistoolkitforquantitativeproteomicsdata