View source: R/vis_identifier.R
vis_identifier_grp_surv | R Documentation |
NOTE: the dataset must be dense matrix in UCSC Xena data hubs.
vis_identifier_grp_surv( dataset = NULL, id = NULL, surv_df, samples = NULL, cutoff_mode = c("Auto", "Custom", "None"), cutpoint = c(50, 50), palette = "aaas", ... )
dataset |
the dataset to obtain identifiers. |
id |
the molecule identifier. |
surv_df |
a
|
samples |
default is |
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 |
palette |
color palette, can be "hue", "grey", "RdBu", "Blues", "npg", "aaas", etc.
More see |
... |
other parameters passing to |
a (gg)plot object.
## 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)
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