vis_pcawg_gene_cor: Visualize Gene-Gene Correlation in TCGA

Description

Visualize Gene-Gene Correlation in TCGA

Usage

vis_pcawg_gene_cor(
  Gene1 = "CSF1R",
  Gene2 = "JAK3",
  data_type1 = "mRNA",
  data_type2 = "mRNA",
  cor_method = "spearman",
  purity_adj = TRUE,
  use_log_x = FALSE,
  use_log_y = FALSE,
  use_regline = TRUE,
  dcc_project_code_choose = "BLCA-US",
  use_all = FALSE,
  filter_tumor = TRUE,
  alpha = 0.5,
  color = "#000000",
  opt_pancan = .opt_pancan
)

Value

a ggplot object

Arguments

Gene1: a molecular identifier (e.g., "TP53") or a formula specifying genomic signature ("TP53 + 2 * KRAS - 1.3 * PTEN").
Gene2: a molecular identifier (e.g., "TP53") or a formula specifying genomic signature ("TP53 + 2 * KRAS - 1.3 * PTEN").
data_type1: choose gene profile type for the first gene, including "mRNA","transcript","methylation","miRNA","protein","cnv_gistic2"
data_type2: choose gene profile type for the second gene, including "mRNA","transcript","methylation","miRNA","protein","cnv_gistic2"
cor_method: correlation method
purity_adj: whether performing partial correlation adjusted by purity
use_log_x: if TRUE, log X values.
use_log_y: if TRUE, log Y values.
use_regline: if TRUE, add regression line.
dcc_project_code_choose: select project code.
use_all: use all sample, default FALSE.
filter_tumor: whether use tumor sample only, default TRUE
alpha: dot alpha.
color: dot color.
opt_pancan: specify one dataset for some molercular profiles