metamorphr

metamorphr-package

<img src="figures/logo.png?package=metamorphr&version=0.2.0" style="float: right" alt="logo" width="120">
Facilitate tasks typically encountered during metabolomics data analysis including data import, filtering, missing value imputation (Stacklies et al. (2007) tools:::Rd_expr_doi("10.1093/bioinformatics/btm069"), Stekhoven et al. (2012) tools:::Rd_expr_doi("10.1093/bioinformatics/btr597"), Tibshirani et al. (2017) tools:::Rd_expr_doi("10.18129/B9.BIOC.IMPUTE"), Troyanskaya et al. (2001) tools:::Rd_expr_doi("10.1093/bioinformatics/17.6.520")), normalization (Bolstad et al. (2003) tools:::Rd_expr_doi("10.1093/bioinformatics/19.2.185"), Dieterle et al. (2006) tools:::Rd_expr_doi("10.1021/ac051632c"), Zhao et al. (2020) tools:::Rd_expr_doi("10.1038/s41598-020-72664-6")) transformation, centering and scaling (Van Den Berg et al. (2006) tools:::Rd_expr_doi("10.1186/1471-2164-7-142")) as well as statistical tests and plotting. 'metamorphr' introduces a tidy (Wickham et al. (2019) tools:::Rd_expr_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'.

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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

Tidy and Streamlined Metabolomics Data Workflows

metamorphr-package function

Maintainer: Yannik Schermer <a href="/link/yannik.schermer%40chem.rptu.de?package=metamorphr&version=0.2.0" data-mini-rdoc="metamorphr::yannik.schermer@chem.rptu.de">yannik.schermer@chem.rptu.de</a> (<a href="https://orcid.org/0009-0002-5201-057X">ORCID</a>) [copyright holder]

Author

<img src='figures/logo.png' style='float: right' alt='logo' width='120' />
Facilitate tasks typically encountered during metabolomics data analysis including data import, filtering, missing value imputation (Stacklies et al. (2007) tools:::Rd_expr_doi("10.1093/bioinformatics/btm069"), Stekhoven et al. (2012) tools:::Rd_expr_doi("10.1093/bioinformatics/btr597"), Tibshirani et al. (2017) tools:::Rd_expr_doi("10.18129/B9.BIOC.IMPUTE"), Troyanskaya et al. (2001) tools:::Rd_expr_doi("10.1093/bioinformatics/17.6.520")), normalization (Bolstad et al. (2003) tools:::Rd_expr_doi("10.1093/bioinformatics/19.2.185"), Dieterle et al. (2006) tools:::Rd_expr_doi("10.1021/ac051632c"), Zhao et al. (2020) tools:::Rd_expr_doi("10.1038/s41598-020-72664-6")) transformation, centering and scaling (Van Den Berg et al. (2006) tools:::Rd_expr_doi("10.1186/1471-2164-7-142")) as well as statistical tests and plotting. 'metamorphr' introduces a tidy (Wickham et al. (2019) tools:::Rd_expr_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'.

metamorphr: Tidy and Streamlined Metabolomics Data Workflows — metamorphr-package

Maintainer: Yannik Schermer <a href='mailto:yannik.schermer@chem.rptu.de'>yannik.schermer@chem.rptu.de</a> (<a href='https://orcid.org/0009-0002-5201-057X'>ORCID</a>) [copyright holder]

metamorphr-package: metamorphr: Tidy and Streamlined Metabolomics Data Workflows

Description

Arguments

Author

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