Chapter 20
The jPOST Repository as a Public Data Repository
for Shotgun Proteomics
Yu Watanabe, Akiyasu C. Yoshizawa, Yasushi Ishihama,
and Shujiro Okuda
Abstract
In recent years, mass spectrometry-based proteomics approach has made significant progress and the
number of datasets related to various proteomics projects has increased worldwide. To promote the sharing
and reuse of promising datasets, it is important to build an appropriate, high-quality public data repository.
For this purpose, several repositories have already been created. The jPOST repository that we developed in
2016 has successfully implemented several unique features, such as fast file upload, flexible file management,
and an easy-to-use interface. In addition, this repository is an official member of the ProteomeXchange
Consortium established to facilitate standard data submission and global dissemination of mass spectrometry proteomics data. Our repository contributes to the global partnership for sharing and storing all the
datasets related to various proteomics experiments.
Key words Proteomics, Mass spectrometry, Repository, Database, ProteomeXchange Consortium
1 Introduction
For the mass spectrometry-based proteomics studies, which have
been widely conducted in recent years, while publishing the
obtained results to a scientific journal, it is necessary to register
the raw data of the mass spectrometry experiments in a public data
repository [1]. Although there are several reasons for this, the first
and foremost is that the re-analysis of raw data is necessary for
performing meta-analysis of data that have been acquired from
multiple different projects. In addition, raw data are also required
to verify the previously analyzed results. Furthermore, many raw
data are indispensable for the development of better data analysis
methods, for instance, in the database search engines. As an example, the Global Proteome Machine (GPM) provides results that are
generated by reanalyzing raw data obtained from public repositories and provides the researchers with an opportunity to selfassess the validity of their experimental results [2]. In addition,
Mo ´ nica Carrera and Jesu ´ s Mateos (eds.), Shotgun Proteomics: Methods and Protocols, Methods in Molecular Biology, vol. 2259,
https://doi.org/10.1007/978-1-0716-1178-4_20, © Springer Science+Business Media, LLC, part of Springer Nature 2021
309
The jPOST Repository as a Public Data Repository
for Shotgun Proteomics
Yu Watanabe, Akiyasu C. Yoshizawa, Yasushi Ishihama,
and Shujiro Okuda
Abstract
In recent years, mass spectrometry-based proteomics approach has made significant progress and the
number of datasets related to various proteomics projects has increased worldwide. To promote the sharing
and reuse of promising datasets, it is important to build an appropriate, high-quality public data repository.
For this purpose, several repositories have already been created. The jPOST repository that we developed in
2016 has successfully implemented several unique features, such as fast file upload, flexible file management,
and an easy-to-use interface. In addition, this repository is an official member of the ProteomeXchange
Consortium established to facilitate standard data submission and global dissemination of mass spectrometry proteomics data. Our repository contributes to the global partnership for sharing and storing all the
datasets related to various proteomics experiments.
Key words Proteomics, Mass spectrometry, Repository, Database, ProteomeXchange Consortium
1 Introduction
For the mass spectrometry-based proteomics studies, which have
been widely conducted in recent years, while publishing the
obtained results to a scientific journal, it is necessary to register
the raw data of the mass spectrometry experiments in a public data
repository [1]. Although there are several reasons for this, the first
and foremost is that the re-analysis of raw data is necessary for
performing meta-analysis of data that have been acquired from
multiple different projects. In addition, raw data are also required
to verify the previously analyzed results. Furthermore, many raw
data are indispensable for the development of better data analysis
methods, for instance, in the database search engines. As an example, the Global Proteome Machine (GPM) provides results that are
generated by reanalyzing raw data obtained from public repositories and provides the researchers with an opportunity to selfassess the validity of their experimental results [2]. In addition,
Mo ´ nica Carrera and Jesu ´ s Mateos (eds.), Shotgun Proteomics: Methods and Protocols, Methods in Molecular Biology, vol. 2259,
https://doi.org/10.1007/978-1-0716-1178-4_20, © Springer Science+Business Media, LLC, part of Springer Nature 2021
309