impute_user_value

Replace missing intensity values (<code>NA</code>) with a user-provided value (e.g., 1).

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_user_value function

<dl><dt>data</dt>
<dd>A tidy tibble created by <code>read_featuretable</code>.</dd>
<dt>value</dt>
<dd>Numeric that replaces missing values</dd></dl>

Arguments

Impute missing values by replacing them with a user-provided value — impute_user_value

<dl>

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


<dt>value</dt>
<dd>Numeric that replaces missing values</dd>

</dl>

impute_user_value: Impute missing values by replacing them with a user-provided value

Description

Usage

Value

Arguments

Examples