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Supported file formats

MS-MINT is designed to support a variety of mass spectrometry (MS) data formats by converting them into a standardized tabular format for downstream analysis. Here's a breakdown of the file types you can use with MS-MINT, based on your code:

Supported File Formats in MS-MINT

Format Extension Description Read By Function
mzXML .mzxml An older open XML-based format for MS data. mzxml_to_df()
mzML .mzml Widely used open standard for MS data (XML-based). mzml_to_df()
mzMLb .mzmlb A binary-efficient variant of mzML (faster, smaller). mzmlb_to_df__pyteomics()
HDF5 .hdf, .h5 Hierarchical format often used for storing large numerical datasets. pd.read_hdf()
Feather .feather Fast, lightweight binary format for DataFrames (used with Arrow). pd.read_feather()
Parquet .parquet Columnar data format for fast read and compression. pd.read_parquet()

How It Works

The function ms_file_to_df() acts as a universal file loader. It:

  1. Detects the file extension (e.g., .mzML, .hdf, etc.)
  2. Dispatches to the appropriate reader (e.g., mzml_to_df, read_parquet)
  3. Normalizes the schema to include the following standard columns:
["scan_id", "ms_level", "polarity", "scan_time", "mz", "intensity"]

These columns are crucial for MS-MINT processing and analysis.

Special Cases and Notes

  • Time Unit Handling:

  • mzXML and mzML files may report scan times in minutes, but MS-MINT normalizes this to seconds.

  • Thermo RAW Parquet Files:

  • If you load a .parquet file not already in MS-MINT format, MS-MINT attempts to reformat it using format_thermo_raw_file_reader_parquet().

  • mzMLb Support:

  • Only works if the optional dependency pyteomics.mzmlb is available.
  • If not installed, MS-MINT will log a warning but still function for other formats.