transform_log

Log-transforms intensities. The default (base = 10) calculates the log10.
This transformation can help reduce heteroscedasticity. See references for more information.

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

transform_log function

<dl><dt>data</dt>
<dd>A tidy tibble created by <code>read_featuretable</code>.</dd>
<dt>base</dt>
<dd>Which base should be used for the log-transformation. The default (10) means that log10 values of the intensities are calculated.</dd></dl>

Arguments

Transforms the intensities by calculating their log — transform_log

<dl>

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


<dt>base</dt>
<dd>Which base should be used for the log-transformation. The default (10) means that log10 values of the intensities are calculated.</dd>

</dl>

transform_log: Transforms the intensities by calculating their log

Description

Usage

Value

Arguments

References

Examples