mwang87
October 3, 2018, 12:45am
1
q2-metabolomics is a tool to import metabolomics data into qiime2 to perform analysis. This is accomplished in one of three ways:
Given mzXML/mzML mass spectrometry files, MS2 spectrum count is generated by automatically analyzing data with GNPS (gnps.ucsd.edu) and outputs feature table qza
Already analyzed with molecular networking in GNPS, import given a task identifier outputting a feature table qza
Mass spectrometry MS1 features integrated with mzmine2 and outputting a feature table qza
q2-metabolomics: GitHub - mwang87/q2_metabolomics
Installing q2-metabolomics
conda install -c mwang87 q2-metabolomics
Checkout out more extensive readme for examples and tutorial!
[](https://travis-ci.com/mwang87/q2_metabolomics)
This is a Qiime2 plugin to analyze metabolomics data that utilizes GNPS.
## Background
Mass spectrometry detects molecules via charged surrogates called ions (i.e. mass-to-charge, m/z). MS data contains MS1 spectra (i.e. spectrum of all ions; m/z and their respective abundance) and MS2 spectra (i.e. spectrum of structural fragments of an ion). MS2. spectra are generated by imparting excess internal energy into ions which causes them to dissociate into smaller mass fragments. Collision induced dissociation (CID) or higher-energy collision induced dissociation (HCD) are common methods applied to non-volatile ionized molecules to impart energy via collisions with gas molecules. One can collect both MS1 and MS2 spectra in a single experiment using data dependent acquisition (DDA), a common approach used in untargeted metabolomics. The data contains a series of MS1 spectra from which the n most abundant m/z values are selected and fragmented serially. This cycle continues throughout the analysis of a sample. Often, liquid chromatography (or chemical separation techniques) are combined with mass spectrometry to i) simplify sample complexity, ii) provide orthogonal information (e.g. retention time), and iii) increase coverage of the fragmentation approach to fragment more unique ions (e.g. isomers separated by chromatography can all be fragmented individually). Samples can be compared qualitatively and/or quantitatively using either MS1 or MS2 data or a combination of the two.
### MS2 Spectral Counts
If one were to collect data using DDA or similar method, multiple MS2 spectra from the sample ion (aka molecule) can be present in the data. One of the initial data analysis processes performed in GNPS (via MScluster) is to collapse identical spectra into a single molecular feature. The number of fragmentation spectra measured for each molecular feature (unique ion) per sample, i.e. spectral counts, can be used as a semiquantitative estimate: i.e. the higher the spectral count, the more abundant the molecular feature will be as it triggered multiple fragmentation events.
### MS1 Peak Areas
Fundamentally, spectral abundance observed at a given time in a mass spectrum is related to concentration (imperfectly); however, integration of spectral abundance over time better represents the concentration of a particular compound in the sample. Extraction ion chromatograms (XIC) are generated from all observed m/z in the MS1 of a sample, and the area under the curve (i.e. peak area) are determined via integration. Advantage of comparing samples using the MS1 peak area is that the quantitative information can be more accurate as well as more sensitively, particularly for those compounds of low abundance, as not all ions will be selected in the top n most abundant peaks and thus not trigger a MS2 fragmentation event.
## Installation
Install Qiime2 and activate environment by following the steps described [here](https://docs.qiime2.org/2018.6/install/native/).
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Let us know if there are any issues, suggestions, or any feedback.
Ming
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thermokarst
December 20, 2019, 1:57am
2
2 posts were split to a new topic: Can't find q2-metabolomics plugin