vis_identifier_grp_surv {UCSCXenaShiny}

Visualize Identifier Group Survival Difference

Description

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

Usage

vis_identifier_grp_surv(
  dataset = NULL,
  id = NULL,
  surv_df,
  samples = NULL,
  cutoff_mode = c("Auto", "Custom", "None"),
  cutpoint = c(50, 50),
  palette = "aaas",
  ...
)

Arguments

dataset

the dataset to obtain identifiers.

id

the molecule identifier.

surv_df

a data.frame. The "time" should be in unit of "days".

• If there are 3 columns, the names should be "sample", "time", "status".

• If there are 4 columns, the names should be "sample", "value", "time", "status".

samples

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

cutoff_mode

mode for grouping samples, can be "Auto" (default) or "Custom" or "None" (for groups have been prepared).

cutpoint

cut point (in percent) for "Custom" mode, default is c(50, 50).

palette

color palette, can be "hue", "grey", "RdBu", "Blues", "npg", "aaas", etc. More see ?survminer::ggsurvplot.

...

other parameters passing to survminer::ggsurvplot

Value

a (gg)plot object.

Examples

## Not run: 
library(UCSCXenaTools)
expr_dataset <- "TCGA.LUAD.sampleMap/HiSeqV2_percentile"
cli_dataset <- "TCGA.LUAD.sampleMap/LUAD_clinicalMatrix"
id <- "KRAS"
cli_df <- XenaGenerate(
  subset = XenaDatasets == "TCGA.LUAD.sampleMap/LUAD_clinicalMatrix"
) %>%
  XenaQuery() %>%
  XenaDownload() %>%
  XenaPrepare()

# Use individual survival data
surv_df1 <- cli_df[, c("sampleID", "ABSOLUTE_Ploidy", "days_to_death", "vital_status")]
surv_df1$vital_status <- ifelse(surv_df1$vital_status == "DECEASED", 1, 0)
vis_identifier_grp_surv(surv_df = surv_df1)

# Use both dataset argument and vis_identifier_grp_surv(surv_df = surv_df1)
surv_df2 <- surv_df1[, c(1, 3, 4)]
vis_identifier_grp_surv(expr_dataset, id, surv_df = surv_df2)
vis_identifier_grp_surv(expr_dataset, id,
  surv_df = surv_df2,
  cutoff_mode = "Custom", cutpoint = c(25, 75)
)

## End(Not run)