toy_metaboscape

The raw feature table is also included.
This tibble can be reproduced with <code>metamorphr::read_featuretable(system.file("extdata", "toy_metaboscape.csv", package = "metamorphr"), metadata_cols = 2:5)</code>.

datasets

Facilitate tasks typically encountered during metabolomics data analysis including data import, filtering, missing value imputation (Stacklies et al. (2007) <doi:10.1093/bioinformatics/btm069>, Stekhoven et al. (2012) <doi:10.1093/bioinformatics/btr597>, Tibshirani et al. (2017) <doi:10.18129/B9.BIOC.IMPUTE>, Troyanskaya et al. (2001) <doi:10.1093/bioinformatics/17.6.520>), normalization (Bolstad et al. (2003) <doi:10.1093/bioinformatics/19.2.185>, Dieterle et al. (2006) <doi:10.1021/ac051632c>, Zhao et al. (2020) <doi:10.1038/s41598-020-72664-6>) transformation, centering and scaling (Van Den Berg et al. (2006) <doi:10.1186/1471-2164-7-142>) as well as statistical tests and plotting. 'metamorphr' introduces a tidy (Wickham et al. (2019) <doi:10.21105/joss.01686>) format for metabolomics data and is designed to make it easier to build elaborate analysis workflows and to integrate them with 'tidyverse' packages including 'dplyr' and 'ggplot2'.

Yannik Schermer

metamorphr

Tidy and Streamlined Metabolomics Data Workflows

toy_metaboscape function

<div class="section" id="toy-metaboscape">
<h3><code>toy_metaboscape</code></h3>
A data frame with 110 rows and 8 columns:<dl>
<dt>UID</dt>
<dd>A unique identifier for each Feature. This column is automatically generated by <code>metamorphr::read_featuretable()</code> when the feature table is imported.</dd><dt>Feature</dt>
<dd>A label given to each Feature for easier identification. The column of the original feature table that is used to generate the Feature column is specified with the <code>label_col</code> argument of <code>metamorphr::read_featuretable()</code>.</dd><dt>Sample</dt>
<dd>Sample name. Column names in the original feature table.</dd><dt>Intensity</dt>
<dd>Measured intensity (or area).</dd><dt>RT</dt>
<dd>Retention time. Feature metadata and therefore not really necessary.</dd><dt>m/z</dt>
<dd>Mass over charge. Feature metadata and therefore not really necessary.</dd><dt>Name</dt>
<dd>Feature name. Feature metadata and therefore not really necessary.</dd><dt>Formula</dt>
<dd>Chemical formula. Feature metadata and therefore not really necessary.</dd>...</dl></div>

Format

A small toy data set created from a feature table in MetaboScape style — toy_metaboscape

<div class='section' id='toy-metaboscape'>
<h3><code>toy_metaboscape</code></h3>


A data frame with 110 rows and 8 columns:<dl>
<dt>UID</dt>
<dd>A unique identifier for each Feature. This column is automatically generated by <code>metamorphr::read_featuretable()</code> when the feature table is imported.</dd>

<dt>Feature</dt>
<dd>A label given to each Feature for easier identification. The column of the original feature table that is used to generate the Feature column is specified with the <code>label_col</code> argument of <code>metamorphr::read_featuretable()</code>.</dd>

<dt>Sample</dt>
<dd>Sample name. Column names in the original feature table.</dd>

<dt>Intensity</dt>
<dd>Measured intensity (or area).</dd>

<dt>RT</dt>
<dd>Retention time. Feature metadata and therefore not really necessary.</dd>

<dt>m/z</dt>
<dd>Mass over charge. Feature metadata and therefore not really necessary.</dd>

<dt>Name</dt>
<dd>Feature name. Feature metadata and therefore not really necessary.</dd>

<dt>Formula</dt>
<dd>Chemical formula. Feature metadata and therefore not really necessary.</dd>

...

</dl>

</div>

toy_metaboscape: A small toy data set created from a feature table in MetaboScape style

Description

Usage

Arguments

Format

`toy_metaboscape`