UCSCXenaShiny (version 2.1.0)

vis_identifier_cor: Visualize Identifier-Identifier Correlation

Description

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

Usage

vis_identifier_cor(
  dataset1,
  id1,
  dataset2,
  id2,
  samples = NULL,
  use_ggstats = FALSE,
  use_simple_axis_label = TRUE,
  line_color = "blue",
  alpha = 0.5,
  ...
)

Value

a (gg)plot object.

Arguments

dataset1

the dataset to obtain id1.

id1

the first molecule identifier.

dataset2

the dataset to obtain id2.

id2

the second molecule identifier.

samples

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

use_ggstats

if TRUE, use ggstatsplot package for plotting.

use_simple_axis_label

if TRUE (default), use simple axis labels. Otherwise, data subtype will be labeled.

line_color

set the color for regression line.

alpha

set the alpha for dots.

...

other parameters passing to ggscatter.

Examples

if (FALSE) {
dataset <- "TcgaTargetGtex_rsem_isoform_tpm"
id1 <- "TP53"
id2 <- "KRAS"
vis_identifier_cor(dataset, id1, dataset, id2)

samples <- c(
  "TCGA-D5-5538-01", "TCGA-VM-A8C8-01",
  "TCGA-ZN-A9VQ-01", "TCGA-EE-A17X-06",
  "TCGA-05-4420-01"
)
vis_identifier_cor(dataset, id1, dataset, id2, samples)

dataset1 <- "TCGA-BLCA.htseq_counts.tsv"
dataset2 <- "TCGA-BLCA.gistic.tsv"
id1 <- "TP53"
id2 <- "KRAS"
vis_identifier_cor(dataset1, id1, dataset2, id2)
}