https://github.com/coayala/cmmrt_app

Pipeline for annotation with the CMM-RT pipeline

https://github.com/coayala/cmmrt_app

Science Score: 39.0%

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Repository

Pipeline for annotation with the CMM-RT pipeline

Basic Info
  • Host: GitHub
  • Owner: Coayala
  • License: mit
  • Language: Python
  • Default Branch: main
  • Size: 18.7 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 1 year ago · Last pushed about 1 year ago
Metadata Files
Readme License

README.md

Metabolite annotation based on RT prediction and projection

The Dash app in this repository allows for the annotation of metabolites based on retention time prediction and projection, based on the method described in:

  • García, C.A., Gil-de-la-Fuente, A., Barbas, C. et al. Probabilistic metabolite annotation using retention time prediction and meta-learned projections. J Cheminform 14, 33 (2022). https://doi.org/10.1186/s13321-022-00613-8

App setup and installation

A conda environment is provided to be able to install and run both the original CMM-RT pipeline as well as this app.

1. Create conda environment

The conda environment can be created by cloning this repository as follows

git clone https://github.com/Coayala/cmmrt_app.git cd cmmrt_app mamba create -n cmmrt_app mamba env update -n cmmrt_app --file environment.yml

2. Install the CMM-RT package

git clone https://github.com/constantino-garcia/cmmrt.git cd cmmrt make install

Running the app

The app requires two files to run: 1. A csv files with all detected metabolites. File must have columns for their FeatureID, calc_mw (Exact Mass), and rt. 2. A csv file with at least 20 metabolites that have been previously identified. File must have columns for their FeatureID, calc_mw (Exact Mass), rt, and annot_id (with PubChem IDs). Example files provided in the data/example_files folder.

The app can be started by running:

cd cmmrt_app/ python app.py

Owner

  • Name: Christian Ayala-Ortiz
  • Login: Coayala
  • Kind: user
  • Company: @tfaily-lab

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