boxplotTCGA: Create Boxplots for TCGA Datasets

In RTCGA/RTCGA: The Cancer Genome Atlas Data Integration

Create Boxplots for TCGA Datasets

Description

Function creates boxplots (geom_boxplot) for TCGA Datasets.

Usage

boxplotTCGA(
  data,
  x,
  y,
  fill = x,
  coord.flip = TRUE,
  facet.names = NULL,
  ylab = y,
  xlab = x,
  legend.title = xlab,
  legend = "top",
  ...,
  ggtheme = theme_RTCGA()
)

Arguments

data	A data.frame from TCGA study containing variables to be plotted.
x	A character name of variable containing groups.
y	A character name of continous variable to be plotted.
fill	A character names of fill variable. By default, the same as x.
coord.flip	Whether to flip coordinates.
facet.names	A character of length maximum 2 containing names of variables to produce facets. See examples.
ylab	The name of y label. Remember about coord.flip.
xlab	The name of x label. Remember about coord.flip.
legend.title	A character with legend's title.
legend	A character specifying legend position. Allowed values are one of c("top", "bottom", "left", "right", "none"). Default is "top" side position. to remove the legend use legend = "none".
...	Further arguments passed to geom_boxplot.
ggtheme	a ggtheme to be used (set to NULL, if using ggthemr package)

Issues

If you have any problems, issues or think that something is missing or is not clear please post an issue on https://github.com/RTCGA/RTCGA/issues.

Author(s)

Marcin Kosinski, [e-mail]

See Also

RTCGA website http://rtcga.github.io/RTCGA/articles/Visualizations.html.

Other RTCGA: RTCGA-package, checkTCGA(), convertTCGA(), datasetsTCGA, downloadTCGA(), expressionsTCGA(), heatmapTCGA(), infoTCGA(), installTCGA(), kmTCGA(), mutationsTCGA(), pcaTCGA(), readTCGA(), survivalTCGA(), theme_RTCGA()

Examples

library(RTCGA)
library(RTCGA.rnaseq)
# perfrom plot
library(dplyr)
expressionsTCGA(ACC.rnaseq, BLCA.rnaseq, BRCA.rnaseq, OV.rnaseq,
  extract.cols = "MET|4233") %>%
  rename(cohort = dataset,
  MET = `MET|4233`) %>%  
  #cancer samples
  filter(substr(bcr_patient_barcode, 14, 15) == "01") -> ACC_BLCA_BRCA_OV.rnaseq
  

boxplotTCGA(ACC_BLCA_BRCA_OV.rnaseq, "cohort", "MET")
boxplotTCGA(ACC_BLCA_BRCA_OV.rnaseq, "cohort", "log1p(MET)")
boxplotTCGA(ACC_BLCA_BRCA_OV.rnaseq, "reorder(cohort,log1p(MET), median)", "log1p(MET)")
boxplotTCGA(ACC_BLCA_BRCA_OV.rnaseq, "reorder(cohort,log1p(MET), max)", "log1p(MET)")
boxplotTCGA(ACC_BLCA_BRCA_OV.rnaseq, "reorder(cohort,log1p(MET), median)", "log1p(MET)",
            xlab = "Cohort Type", ylab = "Logarithm of MET")
boxplotTCGA(ACC_BLCA_BRCA_OV.rnaseq, "reorder(cohort,log1p(MET), median)", "log1p(MET)", 
            xlab = "Cohort Type", ylab = "Logarithm of MET", legend.title = "Cohorts")
boxplotTCGA(ACC_BLCA_BRCA_OV.rnaseq, "reorder(cohort,log1p(MET), median)", "log1p(MET)", 
            xlab = "Cohort Type", ylab = "Logarithm of MET", 
            legend.title = "Cohorts", legend = "bottom")

## facet example
library(RTCGA.mutations)
library(dplyr)
mutationsTCGA(BRCA.mutations, OV.mutations, ACC.mutations, BLCA.mutations) %>% 
  filter(Hugo_Symbol == 'TP53') %>%
  filter(substr(bcr_patient_barcode, 14, 15) == "01") %>% # cancer tissue
  mutate(bcr_patient_barcode = substr(bcr_patient_barcode, 1, 12)) -> 
  ACC_BLCA_BRCA_OV.mutations

mutationsTCGA(BRCA.mutations, OV.mutations, ACC.mutations, BLCA.mutations) -> 
  ACC_BLCA_BRCA_OV.mutations_all

ACC_BLCA_BRCA_OV.rnaseq %>%
  mutate(bcr_patient_barcode = substr(bcr_patient_barcode, 1, 15)) %>%
  filter(bcr_patient_barcode %in% 
  substr(ACC_BLCA_BRCA_OV.mutations_all$bcr_patient_barcode, 1, 15)) %>%
  # took patients for which we had any mutation information
  # so avoided patients without any information about mutations
  mutate(bcr_patient_barcode = substr(bcr_patient_barcode, 1, 12)) %>%
  # strin_length(ACC_BLCA_BRCA_OV.mutations$bcr_patient_barcode) == 12
  left_join(ACC_BLCA_BRCA_OV.mutations,
  by = "bcr_patient_barcode") %>% #joined only with tumor patients
  mutate(TP53 = ifelse(!is.na(Variant_Classification), "Mut", "WILD")) %>%
  select(cohort, MET, TP53) -> ACC_BLCA_BRCA_OV.rnaseq_TP53mutations

boxplotTCGA(ACC_BLCA_BRCA_OV.rnaseq_TP53mutations, "reorder(cohort,log1p(MET), median)",
            "log1p(MET)", xlab = "Cohort Type", ylab = "Logarithm of MET", 
            legend.title = "Cohorts", legend = "bottom", facet.names = c("TP53"))

boxplotTCGA(ACC_BLCA_BRCA_OV.rnaseq_TP53mutations, "reorder(cohort,log1p(MET), median)",
            "log1p(MET)", xlab = "Cohort Type", ylab = "Logarithm of MET",
            legend.title = "Cohorts", legend = "bottom", fill = c("TP53"))

RTCGA/RTCGA documentation built on Nov. 1, 2022, 8:15 p.m.