iProX in 2021: connecting proteomics data sharing with big data

Author:

Chen Tao1,Ma Jie1ORCID,Liu Yi1,Chen Zhiguang2,Xiao Nong2,Lu Yutong2,Fu Yinjin2,Yang Chunyuan1,Li Mansheng1,Wu Songfeng1,Wang Xue1,Li Dongsheng1,He Fuchu1,Hermjakob Henning13ORCID,Zhu Yunping14ORCID

Affiliation:

1. State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China

2. School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou 26469, China

3. European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK

4. Basic Medical School, Anhui Medical University, Anhui 230032, China

Abstract

Abstract The rapid development of proteomics studies has resulted in large volumes of experimental data. The emergence of big data platform provides the opportunity to handle these large amounts of data. The integrated proteome resource, iProX (https://www.iprox.cn), which was initiated in 2017, has been greatly improved with an up-to-date big data platform implemented in 2021. Here, we describe the main iProX developments since its first publication in Nucleic Acids Research in 2019. First, a hyper-converged architecture with high scalability supports the submission process. A hadoop cluster can store large amounts of proteomics datasets, and a distributed, RESTful-styled Elastic Search engine can query millions of records within one second. Also, several new features, including the Universal Spectrum Identifier (USI) mechanism proposed by ProteomeXchange, RESTful Web Service API, and a high-efficiency reanalysis pipeline, have been added to iProX for better open data sharing. By the end of August 2021, 1526 datasets had been submitted to iProX, reaching a total data volume of 92.42TB. With the implementation of the big data platform, iProX can support PB-level data storage, hundreds of billions of spectra records, and second-level latency service capabilities that meet the requirements of the fast growing field of proteomics.

Funder

National Key Research Program of China

Innovation special zone

Program for Guangdong Introducing Innovative and Entrepreneurial Teams

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Genetics

Reference20 articles.

1. Biology: the big challenges of big data;Marx;Nature,2013

2. The challenges of big data biology;Leonelli;Elife,2019

3. The ProteomeXchange consortium in 2020: enabling ‘big data’ approaches in proteomics;Deutsch;Nucleic Acids Res.,2020

4. ProteomeXchange provides globally coordinated proteomics data submission and dissemination;Vizcaíno;Nat. Biotechnol.,2014

5. The PRIDE database and related tools and resources in 2019: improving support for quantification data;Perez-Riverol;Nucleic Acids Res.,2019

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