
The metamorphr package is intended to make working with metabolomics data more fun. For this, metamorphr introduces a tidy data format which stores metabolomics data and associated metadata, as well as MS/MS spectra in one tibble and includes a set of functions to facilitate tasks typically encountered during metabolomics data analysis. This approach allows for an easy integration with Tidyverse packages, including ggplot2 and dplyr.
Install the stable version from CRAN with:
install.packages("metamorphr")Alternatively, you can install the development version of metamorphr from GitHub with:
# install.packages("pak")
pak::pak("yasche/metamorphr")Here is an overview of currently implemented functions.
library(metamorphr)
library(ggplot2)
toy_metaboscape %>%
join_metadata(toy_metaboscape_metadata) %>%
filter_blank(blank_samples = "blank",
blank_as_group = T,
group_column = Group) %>%
filter_grouped_mv(min_found = 0.75) %>%
impute_lod() %>%
normalize_pqn() %>%
scale_auto() %>%
plot_pca(group_column = Group) +
ggplot2::theme_bw()Easily plot the distribution of all intensities across samples
library(dplyr)
toy_metaboscape %>%
join_metadata(toy_metaboscape_metadata) %>%
ggplot2::ggplot(ggplot2::aes(Sample, Intensity, color = Group)) +
ggplot2::geom_boxplot() +
ggplot2::theme_bw()… or compare the intensity of specific features across groups
toy_metaboscape %>%
join_metadata(toy_metaboscape_metadata) %>%
dplyr::filter(Name %in% c("Arachidonic acid", "ADP", "NADPH")) %>%
dplyr::filter(Group %in% c("control", "treatment")) %>%
ggplot2::ggplot(ggplot2::aes(Group, Intensity, color = Group)) +
ggplot2::geom_boxplot() +
ggplot2::facet_wrap(~Name) +
ggplot2::theme_bw()