tcga survival analysis | R Documentation |
Firstly, get merged data of one molecular profile value and associated clinical data from TCGA Pan-Cancer dataset.
Secondly, filter data as your wish.
Finally, show K-M plot.
tcga_surv_get( item, TCGA_cohort = "LUAD", profile = c("mRNA", "miRNA", "methylation", "transcript", "protein", "mutation", "cnv"), TCGA_cli_data = dplyr::full_join(load_data("tcga_clinical"), load_data("tcga_surv"), by = "sample") ) tcga_surv_plot( data, time = "time", status = "status", cutoff_mode = c("Auto", "Custom"), cutpoint = c(50, 50), cnv_type = c("Duplicated", "Normal", "Deleted"), profile = c("mRNA", "miRNA", "methylation", "transcript", "protein", "mutation", "cnv"), palette = "aaas", ... )
item |
a molecular identifier, can be gene symbol (common cases), protein symbol, etc. |
TCGA_cohort |
a TCGA cohort, e.g. "LUAD" (default), "LUSC", "ACC". |
profile |
a molecular profile. Option can be one of "mRNA" (default), "miRNA", "methylation", "transcript", "protein", "mutation", "cnv". |
TCGA_cli_data |
a |
data |
a subset of result from |
time |
the column name for "time". |
status |
the column name for "status". |
cutoff_mode |
mode for grouping samples, can be "Auto" (default) or "Custom". |
cutpoint |
cut point (in percent) for "Custom" mode, default is |
cnv_type |
only used when profile is "cnv", can select from |
palette |
color palette, can be "hue", "grey", "RdBu", "Blues", "npg", "aaas", etc.
More see |
... |
other parameters passing to |
a data.frame
or a plot.
## Not run: # 1. get data data <- tcga_surv_get("TP53") # 2. filter data (optional) # 3. show K-M plot tcga_surv_plot(data, time = "DSS.time", status = "DSS") ## End(Not run)
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