Automated Metadata Extraction from mzML Files with RunAssessor

The reusability of proteomics data sets depends on the ability to obtain accurate metadata to guide reprocessing
pipelines. However, many data sets deposited in public data repositories
lack sufficient and reliable annotation, limiting large-scale reanalyses.
To address this challenge, we developed RunAssessor, a tool that systematically
extracts and summarizes information directly from mass spectrometry
data files prior to peptide identification analysis. RunAssessor extracts
and summarizes sample preparation and instrument acquisition parameters
directly from the data where possible. Using one complete data set
and test files from 18 other data sets as examples, we demonstrate
RunAssessor’s ability to extract instrument models, isobaric
labels, phosphoenrichment, precursor and fragment ion tolerances,
along with the dynamic exclusion time used by the instrument. These
extracted metadata are stored in a comprehensive output file, and
summarized in a standard Sample and Data Relationship Format (SDRF)
file, thereby reducing the burden of manual curation and improving
the reliability of proteomics data set metadata, facilitating the
reuse of public data.