Cargando…
ProteomeExpert: a Docker image-based web server for exploring, modeling, visualizing and mining quantitative proteomic datasets
SUMMARY: The rapid progresses of high-throughput sequencing technology-based omics and mass spectrometry-based proteomics, such as data-independent acquisition and its penetration to clinical studies have generated increasing number of proteomic datasets containing hundreds to thousands of samples....
Autores principales: | , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055226/ https://www.ncbi.nlm.nih.gov/pubmed/33416829 http://dx.doi.org/10.1093/bioinformatics/btaa1088 |
_version_ | 1783680412187361280 |
---|---|
author | Zhu, Tiansheng Chen, Hao Yan, Xishan Wu, Zhicheng Zhou, Xiaoxu Xiao, Qi Ge, Weigang Zhang, Qiushi Xu, Chao Xu, Luang Ruan, Guan Xue, Zhangzhi Yuan, Chunhui Chen, Guo-Bo Guo, Tiannan |
author_facet | Zhu, Tiansheng Chen, Hao Yan, Xishan Wu, Zhicheng Zhou, Xiaoxu Xiao, Qi Ge, Weigang Zhang, Qiushi Xu, Chao Xu, Luang Ruan, Guan Xue, Zhangzhi Yuan, Chunhui Chen, Guo-Bo Guo, Tiannan |
author_sort | Zhu, Tiansheng |
collection | PubMed |
description | SUMMARY: The rapid progresses of high-throughput sequencing technology-based omics and mass spectrometry-based proteomics, such as data-independent acquisition and its penetration to clinical studies have generated increasing number of proteomic datasets containing hundreds to thousands of samples. To analyze these quantitative proteomic datasets and other omics (e.g. transcriptomics and metabolomics) datasets more efficiently and conveniently, we present a web server-based software tool ProteomeExpert implemented in Docker, which offers various analysis tools for experimental design, data mining, interpretation and visualization of quantitative proteomic datasets. ProteomeExpert can be deployed on an operating system with Docker installed or with R language environment. AVAILABILITY AND IMPLEMENTATION: The Docker image of ProteomeExpert is freely available from https://hub.docker.com/r/lifeinfo/proteomeexpert. The source code of ProteomeExpert is also openly accessible at http://www.github.com/guomics-lab/ProteomeExpert/. In addition, a demo server is provided at https://proteomic.shinyapps.io/peserver/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8055226 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-80552262021-04-28 ProteomeExpert: a Docker image-based web server for exploring, modeling, visualizing and mining quantitative proteomic datasets Zhu, Tiansheng Chen, Hao Yan, Xishan Wu, Zhicheng Zhou, Xiaoxu Xiao, Qi Ge, Weigang Zhang, Qiushi Xu, Chao Xu, Luang Ruan, Guan Xue, Zhangzhi Yuan, Chunhui Chen, Guo-Bo Guo, Tiannan Bioinformatics Applications Notes SUMMARY: The rapid progresses of high-throughput sequencing technology-based omics and mass spectrometry-based proteomics, such as data-independent acquisition and its penetration to clinical studies have generated increasing number of proteomic datasets containing hundreds to thousands of samples. To analyze these quantitative proteomic datasets and other omics (e.g. transcriptomics and metabolomics) datasets more efficiently and conveniently, we present a web server-based software tool ProteomeExpert implemented in Docker, which offers various analysis tools for experimental design, data mining, interpretation and visualization of quantitative proteomic datasets. ProteomeExpert can be deployed on an operating system with Docker installed or with R language environment. AVAILABILITY AND IMPLEMENTATION: The Docker image of ProteomeExpert is freely available from https://hub.docker.com/r/lifeinfo/proteomeexpert. The source code of ProteomeExpert is also openly accessible at http://www.github.com/guomics-lab/ProteomeExpert/. In addition, a demo server is provided at https://proteomic.shinyapps.io/peserver/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-01-08 /pmc/articles/PMC8055226/ /pubmed/33416829 http://dx.doi.org/10.1093/bioinformatics/btaa1088 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial 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 | Applications Notes Zhu, Tiansheng Chen, Hao Yan, Xishan Wu, Zhicheng Zhou, Xiaoxu Xiao, Qi Ge, Weigang Zhang, Qiushi Xu, Chao Xu, Luang Ruan, Guan Xue, Zhangzhi Yuan, Chunhui Chen, Guo-Bo Guo, Tiannan ProteomeExpert: a Docker image-based web server for exploring, modeling, visualizing and mining quantitative proteomic datasets |
title | ProteomeExpert: a Docker image-based web server for exploring, modeling, visualizing and mining quantitative proteomic datasets |
title_full | ProteomeExpert: a Docker image-based web server for exploring, modeling, visualizing and mining quantitative proteomic datasets |
title_fullStr | ProteomeExpert: a Docker image-based web server for exploring, modeling, visualizing and mining quantitative proteomic datasets |
title_full_unstemmed | ProteomeExpert: a Docker image-based web server for exploring, modeling, visualizing and mining quantitative proteomic datasets |
title_short | ProteomeExpert: a Docker image-based web server for exploring, modeling, visualizing and mining quantitative proteomic datasets |
title_sort | proteomeexpert: a docker image-based web server for exploring, modeling, visualizing and mining quantitative proteomic datasets |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055226/ https://www.ncbi.nlm.nih.gov/pubmed/33416829 http://dx.doi.org/10.1093/bioinformatics/btaa1088 |
work_keys_str_mv | AT zhutiansheng proteomeexpertadockerimagebasedwebserverforexploringmodelingvisualizingandminingquantitativeproteomicdatasets AT chenhao proteomeexpertadockerimagebasedwebserverforexploringmodelingvisualizingandminingquantitativeproteomicdatasets AT yanxishan proteomeexpertadockerimagebasedwebserverforexploringmodelingvisualizingandminingquantitativeproteomicdatasets AT wuzhicheng proteomeexpertadockerimagebasedwebserverforexploringmodelingvisualizingandminingquantitativeproteomicdatasets AT zhouxiaoxu proteomeexpertadockerimagebasedwebserverforexploringmodelingvisualizingandminingquantitativeproteomicdatasets AT xiaoqi proteomeexpertadockerimagebasedwebserverforexploringmodelingvisualizingandminingquantitativeproteomicdatasets AT geweigang proteomeexpertadockerimagebasedwebserverforexploringmodelingvisualizingandminingquantitativeproteomicdatasets AT zhangqiushi proteomeexpertadockerimagebasedwebserverforexploringmodelingvisualizingandminingquantitativeproteomicdatasets AT xuchao proteomeexpertadockerimagebasedwebserverforexploringmodelingvisualizingandminingquantitativeproteomicdatasets AT xuluang proteomeexpertadockerimagebasedwebserverforexploringmodelingvisualizingandminingquantitativeproteomicdatasets AT ruanguan proteomeexpertadockerimagebasedwebserverforexploringmodelingvisualizingandminingquantitativeproteomicdatasets AT xuezhangzhi proteomeexpertadockerimagebasedwebserverforexploringmodelingvisualizingandminingquantitativeproteomicdatasets AT yuanchunhui proteomeexpertadockerimagebasedwebserverforexploringmodelingvisualizingandminingquantitativeproteomicdatasets AT chenguobo proteomeexpertadockerimagebasedwebserverforexploringmodelingvisualizingandminingquantitativeproteomicdatasets AT guotiannan proteomeexpertadockerimagebasedwebserverforexploringmodelingvisualizingandminingquantitativeproteomicdatasets |