checks

check if MS data contains mz and rt, and if MSMS data is present feature names and sample names are identical

A feature clustering algorithm for non-targeted mass spectrometric metabolomics data. This method is compatible with gas and liquid chromatography coupled mass spectrometry, including indiscriminant tandem mass spectrometry data <DOI: 10.1021/ac501530d>.

Helge Hecht

RAMClustR

Mass Spectrometry Metabolomics Feature Clustering and
Interpretation

Corey D. Broeckling

Fayyaz Afsar

Steffen Neumann

Asa Ben-Hur

Jessica Prenni

Matej Trojak

Zargham Ahmad

checks function

<dl><dt>ms1_featureDefinitions</dt>
<dd>dataframe with metadata with columns: mz, rt, feature names containing MS data</dd>
<dt>ms1_featureValues</dt>
<dd>dataframe with rownames = sample names, colnames = feature names containing MS data</dd>
<dt>ms2_featureValues</dt>
<dd>dataframe with rownames = sample names, colnames = feature names containing MSMS data</dd>
<dt>feature_names</dt>
<dd>feature names extracted from the data</dd></dl>

Arguments

checks — checks

<dl>

<dt>ms1_featureDefinitions</dt>
<dd>dataframe with metadata with columns: mz, rt, feature names containing MS data</dd>


<dt>ms1_featureValues</dt>
<dd>dataframe with rownames = sample names, colnames = feature names containing MS data</dd>


<dt>ms2_featureValues</dt>
<dd>dataframe with rownames = sample names, colnames = feature names containing MSMS data</dd>


<dt>feature_names</dt>
<dd>feature names extracted from the data</dd>

</dl>

checks: checks

Description

Usage

Arguments