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.