Visualize Identifier-Identifier Correlation — vis_identifier

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,
  ...
)

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.

Value

a (gg)plot object.

Examples

if (FALSE) { # \dontrun{
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)
} # }