impute_lod

Replace missing intensity values (<code>NA</code>) by what is assumed to be the detector limit of detection (LoD).
It is estimated by dividing the Feature minimum by the provided denominator, usually 5. See the References section 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

impute_lod function

<dl><dt>data</dt>
<dd>A tidy tibble created by <code>read_featuretable</code>.</dd>
<dt>div_by</dt>
<dd>A numeric value that specifies by which number the Feature minimum will be divided</dd></dl>

Arguments

Impute missing values by replacing them with the Feature 'Limit of Detection' — impute_lod

<dl>

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


<dt>div_by</dt>
<dd>A numeric value that specifies by which number the Feature minimum will be divided</dd>

</dl>

impute_lod: Impute missing values by replacing them with the Feature 'Limit of Detection'

Description

Usage

Value

Arguments

References

Examples