The jPOST environment: an integrated proteomics data repository and database

Abstract Rapid progress is being made in mass spectrometry (MS)-based proteomics, yielding an increasing number of larger datasets with higher quality and higher throughput. To integrate proteomics datasets generated from various projects and institutions, we launched a project named jPOST (Japan Pr...

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Bibliographic Details
Published in:Nucleic acids research 2019-01, Vol.47 (D1), p.D1218-D1224
Main Authors: Moriya, Yuki, Kawano, Shin, Okuda, Shujiro, Watanabe, Yu, Matsumoto, Masaki, Takami, Tomoyo, Kobayashi, Daiki, Yamanouchi, Yoshinori, Araki, Norie, Yoshizawa, Akiyasu C, Tabata, Tsuyoshi, Iwasaki, Mio, Sugiyama, Naoyuki, Tanaka, Satoshi, Goto, Susumu, Ishihama, Yasushi
Format: Article
Language:English
Subjects:
Computational Biology - methods
Data Management - methods
Database Issue
Databases, Protein
Humans
Information Storage and Retrieval - methods
Internet
Japan
Mass Spectrometry - methods
Protein Processing, Post-Translational
Proteome - metabolism
Proteomics - methods
User-Computer Interface
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Summary:Abstract Rapid progress is being made in mass spectrometry (MS)-based proteomics, yielding an increasing number of larger datasets with higher quality and higher throughput. To integrate proteomics datasets generated from various projects and institutions, we launched a project named jPOST (Japan ProteOme STandard Repository/Database, https://jpostdb.org/) in 2015. Its proteomics data repository, jPOSTrepo, began operations in 2016 and has accepted more than 10 TB of MS-based proteomics datasets in the past two years. In addition, we have developed a new proteomics database named jPOSTdb in which the published raw datasets in jPOSTrepo are reanalyzed using standardized protocol. jPOSTdb provides viewers showing the frequency of detected post-translational modifications, the co-occurrence of phosphorylation sites on a peptide and peptide sharing among proteoforms. jPOSTdb also provides basic statistical analysis tools to compare proteomics datasets.
ISSN:0305-1048
1362-4962
DOI:10.1093/nar/gky899