mzml2isa - mzML to ISA-tab parsing tool

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for althonos from gravatar.com althonos Avatar for tomnl from gravatar.com tomnl

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: GNU General Public License v3 (GPLv3) (GPLv3)
  • Author: Thomas Lawson, Martin Larralde
  • Tags Metabolomics, Mass spectrometry, metabolites, ISA Tab, mzML, parsing
Classifiers
Report project as malware

Project description

Version Py versions Git Build Status License

Overview

mzml2isa is a Python3 program that can be used to generate an ISA-Tab structure out of mzML files, providing the backbone of a study which can then be edited with an ISA editing tool (see MetaboLights pre-packaged ISA Creator)

Currently the program does the following * Extract meta information from mzML files and store as either python dictionary or JSON format * Create an ISA-Tab file structure with relevant meta information * Add additional metadatas that cannot be parsed from mzML files to the ISA-Tab files through a JSON formatted dictionnary.

Install

With PIP

If pip is installed, it can be used to easily install the parser (this may need to be run as administrator depending on the machine’s architecture):

pip3 install mzml2isa

Without PIP

Alternatively, you can also clone the repository and install from the source :

git clone git://github.com/althonos/mzml2isa && cd mzml2isa
python3 setup.py install

mzml2isa has 2 optional dependencies: progressbar2 and lxml, the latter quickening the parsing process while the other enhances the output of the program. To install them both, use pip:

pip3 install lxml progressbar2

Use

CLI

The parser comes with a simple one-liner:

mzml2isa -i /path/to/mzml_files/ -o /path/to/out_folder/ -s name_of_study

Module

It is also possible to import the package:

from mzml2isa import parsing

in_dir = "/path/to/mzml_files/"
out_dir = "/path/to/out_folder/"
study_identifier_name = "name_of_study"

parsing.full_parse(in_dir, out_dir, study_identifier_name)

Meta extraction

If you just want to extract meta information:

from mzml2isa import mzml

onefile = os.path.join(in_dir,"samp1.mzML")
mm = mzml.mzMLmeta(onefile)

# python dictionary format
print mm.meta

# JSON format
print mm.meta_json

Metabolights

To download some real data from MetaboLights studies to test the converter with, run

python scripts/metabolights-dl.py <size>

from inside the repository, where size is the maximum size in GiB you can allocate to download files. The script will download the files to the example_files/metabolights folder and then run mzml2isa on those files..

If you use a *NIX machine with curlftpfs and bash available, you can also run

scripts/metabolights.sh

to mount the database to the example directory and start converting mzML studies.

Workflow

workflow

Ref

A modified version of the ontology extraction from this blog[1]_ was used, and a slightly modified class from pymzml[2]_

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page