4.1. Main

asari.main.main(parameters={'annotation_filename': 'Annotation_table.tsv', 'asari_version': '1.12.6', 'autoheight': False, 'cal_min_peak_height': 100000, 'check_isotope_ratio': False, 'database_mode': 'auto', 'drop_unaligned_samples': False, 'gaussian_shape': 0.5, 'json_empricalCompounds': '_empCpd_json.json', 'mass_grid_mapping': '_mass_grid_mapping.csv', 'mass_range': (50, 2000), 'max_retention_shift': None, 'min_intensity_threshold': 1000, 'min_peak_height': 100000, 'min_timepoints': 6, 'mode': 'pos', 'multicores': 4, 'mz_tolerance_ppm': 5, 'num_lowess_iterations': 3, 'outdir': 'output', 'output_feature_table': 'Feature_table.tsv', 'peak_area': 'sum', 'peak_number_rt_calibration': 20, 'pickle': False, 'project_name': 'asari_project', 'project_sample_number_small': 10, 'reference': None, 'rt_align_method': 'lowess', 'rt_align_on': True, 'rtime_tolerance': 50, 'signal_noise_ratio': 2, 'wlen': 25})[source]

asari, Trackable and scalable Python program for high-resolution LC-MS metabolomics data preprocessing.

  • analyze: analyze a single mzML file to print summary of statistics and recommended parameters.

  • process: LC-MS data preprocessing

  • xic: construct mass trakcs (chromatogram) from mzML files

  • extract: targeted extraction of given m/z list

  • annotate: annotate a list of features

  • join: merge multiple processed projects (possibly split a large dataset)

  • viz: start interactive data visualization and exploration.

Parameters:

parameters (dict) – This dictionary contains a number of key value pairs that determine the behavior of various aspects of the asari processing. The parameters can be seen in default_parameters.py. Command line arguments will override any defaults and any values provided in the parameters.json file.