ProteomeExpert: a Docker image-based web server for exploring, modeling, visualizing and mining quantitative proteomic datasets

Tiansheng Zhu; Hao Chen; Xishan Yan; Zhicheng Wu; Xiaoxu Zhou; Qi Xiao; Weigang Ge; Qiushi Zhang; Chao Xu; Luang Xu; Guan Ruan; Zhangzhi Xue; Chunhui Yuan; Guo-Bo Chen; Tiannan Guo

doi:10.1093/bioinformatics/btaa1088

ProteomeExpert: a Docker image-based web server for exploring, modeling, visualizing and mining quantitative proteomic datasets

Bioinformatics. 2021 Apr 19;37(2):273-275. doi: 10.1093/bioinformatics/btaa1088.

Authors

Tiansheng Zhu^{1

2

3

4}, Hao Chen^{1

2

5}, Xishan Yan⁶, Zhicheng Wu^{1

2

3

4}, Xiaoxu Zhou^{1

2

3}, Qi Xiao^{1

2

3}, Weigang Ge^{1

2

5}, Qiushi Zhang^{1

2

5}, Chao Xu⁶, Luang Xu^{1

2

3}, Guan Ruan^{1

2

5}, Zhangzhi Xue^{1

2

3}, Chunhui Yuan^{1

2

3}, Guo-Bo Chen^{7

8}, Tiannan Guo^{1

2

3}

Affiliations

¹ Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China.
² Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China.
³ Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China.
⁴ Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, China.
⁵ Westlake Omics (Hangzhou) Biotechnology Co., Ltd., Hangzhou, Zhejiang Province, China.
⁶ College of Mathematics and Informatics, Digital Fujian Institute of Big Data Security Technology, Fujian Normal University, China.
⁷ Clinical Research Institute, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, China.
⁸ Key Laboratory of Endocrine Gland Diseases of Zhejiang Province, Hangzhou, Zhejiang, China.

Abstract

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.

Abstract

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