プログラム

ポスター発表

第4日　5月18日（金）　　ポスター会場

4P-36　　PDF

jPOST: 質量分析生データを最大限に活用するためのメタデータキュレーション

(¹熊本大院生命・ ²新潟大院医歯・ ³DBCLS・ ⁴新潟大産学・ ⁵九大生医研・ ⁶京大院薬・ ⁷京大iPS研・ ⁸トランジット)
^o小林大樹¹・ 荒木令江¹・ 奥田修二郎²・ 渡辺由²・ 守屋勇樹³・ 河野信³・ 山本格⁴・ 松本雅記⁵・ 高見知代⁵・ 吉沢明康⁶・ 田畑剛⁶・ 岩崎未央⁷・ 杉山直幸⁶・ 田中聡⁸・ 五斗進³・ 石濱泰⁶

A large amount of mass spectrometry (MS)-based proteomics data has been generated owing to the recent striking advance in MS instruments and methodology. The construction of management system for these MS files, such as a raw data repository, a standardized re-analysis protocol, and integrated database, is much helpful to publicly utilize these data sets. Here we have initiated the jPOST (Japan ProteOme STandard Repository/Database) project1 to construct such kind of data management system. To fully utilize these MS datasets, the metadata annotation of the MS raw file is important to precisely identify the sample sources, the sample preparation methods, and the MS acquisition settings. However, these metadata are sometimes not in detail, or have inappropriate annotations. First, these files have been divided into each reanalysis unit according to these metadata annotation because raw MS files are re-analyzed to identify peptides/proteins with high quality. Then, these metadata has been converted to the controlled vocabularies used in jPOST database. Especially, we have established the classification method of disease-related samples based on sample types, organs, and disease types. In this presentation, we show some cases of the curation workflow for the metadata annotating jPOST MS files.