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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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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/. |
format | Online Article Text |
id | pubmed-10466079 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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