vis_dim_dist {UCSCXenaShiny}

Visualize the distribution difference of samples after dimension reduction analysis

Description

Visualize the distribution difference of samples after dimension reduction analysis

Usage

vis_dim_dist(
  ids = c("TP53", "KRAS", "PTEN", "MDM2", "CDKN1A"),
  data_type = "mRNA",
  group_info = NULL,
  DR_method = c("PCA", "UMAP", "tSNE"),
  palette = "Set1",
  add_margin = NULL,
  opt_pancan = .opt_pancan
)

Arguments

ids

molecular identifiers (>=3)

data_type

molecular types, refer to query_pancan_value() function

group_info

two-column grouping information with names 'Sample','Group'

DR_method

the dimension reduction method

palette

the color setting of RColorBrewer

add_margin

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

opt_pancan

specify one dataset for some molercular profiles

Value

a ggplot object or rawdata list

Examples

## Not run: 
group_info = tcga_clinical_fine %>% 
  dplyr::filter(Cancer=="BRCA") %>% 
  dplyr::select(Sample, Code) %>% 
  dplyr::rename(Group=Code)

vis_dim_dist(
  ids = c("TP53", "KRAS", "PTEN", "MDM2", "CDKN1A"),
  group_info = group_info
)


## End(Not run)