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Visualize the distribution difference of samples after Molecule Identifier dimensionality reduction analysis

Source: R/vis_identifier_dim_dist.R
vis_identifier_dim_dist.Rd

NOTE: the dataset must be dense matrix in UCSC Xena data hubs.

Usage

vis_identifier_dim_dist(
  dataset = NULL,
  ids = NULL,
  grp_df,
  samples = NULL,
  return.data = FALSE,
  DR_method = c("PCA", "UMAP", "tSNE"),
  add_margin = NULL,
  palette = "Set1"
)

Arguments

dataset

the dataset to obtain identifiers.

ids

the molecule identifiers.

grp_df

When dataset and id are all not NULL, it should be a data.frame with 2 columns.

  • The first column refers to sample ID.

  • The second column refers to groups indicated in axis X.

samples

default is NULL, can be common sample names for two datasets.

return.data

whether to reture the raw meta/matrix data (list) instead of plot

DR_method

the dimensionality reduction method

add_margin

the marginal plot (NULL, "density", "boxplot")

palette

the color setting of RColorBrewer

Value

a ggplot object.

Examples

# vis_identifier_dim_dist(expr_dataset, ids, grp_df, DR_method="PCA")