normalize_median

Normalize across samples by dividing feature intensities by the sample median, making the median 1 in all samples.
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

normalize_median function

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

Arguments

Normalize intensities across samples by dividing by the sample median — normalize_median

<dl>

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

</dl>

normalize_median: Normalize intensities across samples by dividing by the sample median

Description

Usage

Value

Arguments

References

Examples