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Heuristic based feature annotations/identifications of LC-MS metabolomics dataset.

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[![Build Status](https://travis-ci.org/jerkos/mzOS.svg?branch=master)](https://travis-ci.org/jerkos/mzOS) [![Coverage Status](https://coveralls.io/repos/jerkos/mzOS/badge.svg?branch=master&service=github)](https://coveralls.io/github/jerkos/mzOS?branch=master) [![Code Issues](https://www.quantifiedcode.com/api/v1/project/f458ff06e0bd4eb8b2b98cee0dab6ecb/badge.svg)](https://www.quantifiedcode.com/app/project/f458ff06e0bd4eb8b2b98cee0dab6ecb)

## Small library for features annotations in LC-MS metabolomics experiments:

  • [x] isotopes detection

  • [x] adducts/fragments annotation using simple heuristics (when conflicts)

  • [x] database search (HMDB, LMSD) from local sqlite file (fast)

  • [x] database assignment scoring based on predicted isotopic distribution and bayesian algorithm.

  • [ ] functionnal annotation, metabolite pathway enrichment analysis (MPEA)

More details [here](http://jerkos.github.io/mzOS)

## Dependancies

  • numpy

  • scipy

  • scikit-learn

  • pandas

## TODOs:

  • documentation

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