runassessor 0.9.0

A tool to extract empircally identifiable metadata from proteomics mass-spectrometry mzML files prior to identification processing.

RunAssessor

The RunAssessor package provides functionality for assessing a set of input mass spectrometry proteomics mzML files, extracting all information that can be gleaned from the files prior to any attempt to identify the peptides therein.

Installation

Clone the repo and install dependencies:

git clone https://github.com/edeutsch/RunAssessor.git
cd RunAssesor
pip install -r requirements.txt

Quick Start

RunAssessor processes mass spectrometry data in the .mzML format. .mzML.gz files are also supported.

python ~/RunAssessor/bin/assess_mzMLs.py ~/file_path/mass_spec_data.mzML.gz

RunAssessor can also accept multiple .mzML or '.mzML.gz' files at a time

python ~/RunAssessor/bin/assess_mzMLs.py --write_sdrf_files --verbose *.mzML

Running a quick test

In RunAssessor/tests/data/ there is a small .mzML.gz file that can be used to quickly try RunAssessor

cd tests/data
python ../../bin/assess_mzMLs.py chlo_6_tiny.mzML.gz

There is also a set of larger .mzML.gz files of different kinds that are used to test RunAssessor in RunAssessor/tests/large_files/. You can try RunAssessor on those files. Files in large_files will generate a more substantial JSON and summary file compared to chlo_6_tiny.mzML.gz.

cd tests/large_files
python large_test_file_downloader.py
python ../../bin/assess_mzMLs.py *.mzML.gz   # Or single file of your choice

Usage of the main RunAssessor programs

assess_mzMLs.py

The assess_mzMLs.py program is the main RunAssessor program that accepts a set of input mzML files along with various parameters and processes the mzML files accordingly. This is generally the only program that needs to be executed.

Command-line Arguments

Argument	Description	Default	Example
--metadata_filepath	Filename and path of the ouput metadata file. This parameter may be used to change the root name and directory path (relative or absolute) of the output file (affecting the JSON file, the TSV file, optional PDF files and SDRF files)	study_metadata.json	--metadata_filepath ~/PXD123456/PXD123456_metadata.json
--preserve_existing_metadata	If set, read the existing metadata file, preserve its contents, and build on it (default is to overwrite current file).	Not set	--preserve_existing_metadata
--n_threads	Number of files to read in parallel.	Number of CPU cores	--n_threads 4
--write_fragmentation_type_files	If set, writes a fragmentation type file for each mzML input.	Not set	--write_fragmentation_type_files
--verbose	If set, prints more detailed processing information. Use multiple times to increase verbosity.	Not set	--verbose
--version	Prints the version of the script/tool.	Not set	--version
--write_sdrf_file	If set, writes an SDRF file based on the metadata text file.	Not set	--write_sdrf_file
--include_sdrf_provenance	If set, then all information written to the SDRF file will have provenance tags (this is experimental non-standard SDRF, not for routine use).	Not set	--include_sdrf_provenance
--write_pdfs	If set, generates a PDF of delta time and ppm graphs from precursor stats, and a PDF of neutral loss windows from composite intensities.	Not set	--write_pdfs
--write_ions	If set, writes a TSV file of the ion three-sigma table, which lists all fragment ions found.	Not set	--write_ions
--ms_ms_units	Sets units for MS/MS tolerance recommendations: mz or ppm (defaults to ppm for HR and mz for LR)	ppm for HR and mz for LR	--ms_ms_units mz

assess_metadata.py

The assess_metadata.py program reads an existing study_metadata.json file and recomputes recommended parameters and potentially outputs to different formats. This program is generally not routinely used, but can be helpful if, for example, a large set of input files are analyzed and a study_metadata.json file is written, but the --write_sdrf_file was not provided to assess_mzMLs.py. This tool can take the previous analysis and write out the SDRF file based on the existing JSON file, without reprocessing all mzML files again.

Command-line Arguments

Argument	Description	Default	Example
--metadata_file	Specify a metadata file if different than the default.	study_metadata.json	--metadata_file ~/file_path/custom_metadata.json
--write_sdrf_file	If set, writes an SDRF file based on the metadata file. Can be passed multiple times.	Not set	--write_sdrf_file
--verbose	If set, enables verbose output. Use multiple times to increase verbosity.	Not set	--verbose

rename_msruns.py

Renames raw files in current directory to replace special characters in filenames with underscores and writes a mapping document of changes. Some special characters in filename can cause problems in downstream processing tools (for example: spaces, parentheses, ampersands, and more). This program fixes the filenames in a repeatable way and records how the filenames have been adjusted in an output file. This is not needed for normal RunAssessor operation, but may be useful for large-scale reprocessing efforts when certain tools have trouble with special characters in filenames.