Abstract

Poster Presentations

Day 3, May 17（Wed.）　　Room P (Foyer, Room 1004-1007)

3P-28　　PDF

Hive: A new common data format for mass spectrometry and reader API

(Reifycs)
Ipputa Tada, Kazuto Mannen, ^oMitsuhiro Kanazawa, Atsushi Ogiwara

The initial step in data analysis and software development for mass spectrometry is reading the raw measurement data. However, the raw data are non-human readable binary data, and their format varies depending on the type of mass spectrometer used. To address these issues, common XML formats dedicated to mass spectrometry such as mzML, have been used. The XML format is easy for humans to read because it is defined in text; however, it has problems with file size and read/write speed. Here, we introduce our newly developed data format and API for mass spectrometry. This data format solves the limitations in using XML format by utilizing binary data. To address the issue of human readability, we develop an API dedicated to reading this data format that supports Java, Python, and C#. Using this API, users can read mass spectrometry data without being conscious of the variations in mass spectrometers. We also believe that it is suitable for distribution in widely utilized public databases. We expect that the new data format and API will significantly contribute to mass spectrometry data analysis and software development.