ume (version 1.5.2)

uplot_cluster: uplot_cluster

Description

This function plots the results of a cluster analysis and a multi-dimensional scaling (MDS) plot based on the input data. It first creates a hierarchical cluster dendrogram using the Bray-Curtis dissimilarity index, followed by an MDS plot for dimensionality reduction. The function outputs both plots side by side.

Usage

uplot_cluster(mfd, grp = "file_id", int_col = "norm_int", ...)

Value

A named list with two elements:

dendrogram

A recordedplot object containing the hierarchical clustering dendrogram generated from the Bray–Curtis dissimilarity matrix.

mds

A plotly object representing the two-dimensional Multi-Dimensional Scaling (MDS) scatter plot. This can be rendered interactively in HTML or converted to a static ggplot object if needed.

The function always returns a list with these two components.

Arguments

mfd

data.table with molecular formula data as derived from ume::assign_formulas. Column names of elements/isotopes must match names in the isotope column of ume::masses; values are integers representing counts per formula.

grp

Character vector. Names of columns (e.g., sample or file identifiers) used to aggregate results.

int_col

Character. The name of the column that contains the intensity values to be used (e.g. for clustering or color coding). Default usually is "norm_int" for normalized intensity values.

...

Additional arguments passed to methods.

Details

Plot Cluster Analysis and Multi-Dimensional Scaling

See Also

Other plots: uplot_cvm(), uplot_dbe_minus_o_freq(), uplot_dbe_vs_c(), uplot_freq_ma(), uplot_freq_vs_ppm(), uplot_hc_vs_m(), uplot_heteroatoms(), uplot_isotope_precision(), uplot_kmd(), uplot_lcms(), uplot_ma_vs_mz(), uplot_ms(), uplot_n_mf_per_sample(), uplot_pca(), uplot_ratios(), uplot_reproducibility(), uplot_ri_vs_sample(), uplot_vk()

Examples

# Example with demo data
  out <- uplot_cluster(mfd = mf_data_demo, grp = "file", int_col = "norm_int")
  out$dendrogram
  out$mds