scale_center

Centers the intensities of all features around zero using
$$\widetilde{x}_{ij}=x_{ij}-\overline{x}_{i}$$
where $\widetilde{x}_{ij}$ is the intensity of sample $j$, feature $i$ after scaling,
$x_{ij}$ is the intensity of sample $j$, feature $i$ before scaling and $\overline{x}_{i}$ is the mean of intensities of feature $i$ across all samples.
In other words, it subtracts the mean intensity of a feature across samples from the intensities of that feature in each sample.
For more information, see the reference section.

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

scale_center function

<dl><dt>data</dt>
<dd>A tidy tibble created by <code>read_featuretable</code>.</dd></dl>

Arguments

Center intensities of features around zero — scale_center

<dl>

<dt>data</dt>
<dd>A tidy tibble created by <code>read_featuretable</code>.</dd>

</dl>

scale_center: Center intensities of features around zero

Description

Usage

Value

Arguments

References

Examples