RTCGA (version 1.2.2)

expressionsTCGA: Gather Expressions for TCGA Datasets

Description

Function gathers expressions over multiple TCGA datasets and extracts expressions for desired genes. See rnaseq, mRNA, RPPA, miRNASeq, methylation.

Usage

expressionsTCGA(..., extract.cols = NULL, extract.names = TRUE)

Arguments

...

A data.frame or data.frames from TCGA study containing expressions informations.

extract.cols

A character specifing the names of columns to be extracted with bcr_patient_barcode. If NULL (by default) all columns are returned.

extract.names

Logical, whether to extract names of passed data.frames in ....

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.

See Also

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

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

Examples

## for all examples
library(dplyr)
library(tidyr)
library(ggplot2) 

## RNASeq expressions
library(RTCGA.rnaseq)
expressionsTCGA(BRCA.rnaseq, OV.rnaseq, HNSC.rnaseq,
							 extract.cols = "VENTX|27287") %>%
	rename(cohort = dataset,
				 VENTX = `VENTX|27287`) %>%	
 filter(substr(bcr_patient_barcode, 14, 15) == "01") %>% #cancer samples
	ggplot(aes(y = log1p(VENTX),
						 x = reorder(cohort, log1p(VENTX), median),
						 fill = cohort)) + 
	geom_boxplot() +
	theme_RTCGA() +
	scale_fill_brewer(palette = "Dark2")
	
## mRNA expressions	
library(tidyr)
library(RTCGA.mRNA)
expressionsTCGA(BRCA.mRNA, COAD.mRNA, LUSC.mRNA, UCEC.mRNA,
							 extract.cols = c("ARHGAP24", "TRAV20")) %>%
	rename(cohort = dataset) %>%
	select(-bcr_patient_barcode) %>%
	gather(cohort) -> data2plot
names(data2plot)[2] <- "mRNA"
data2plot %>%
	ggplot(aes(y = value,
						 x = reorder(cohort, value, mean),
						 fill = cohort)) + 
	geom_boxplot() +
	theme_RTCGA() +
	scale_fill_brewer(palette = "Set3") +
	facet_grid(mRNA~.) +
	theme(legend.position = "top")


## RPPA expressions
library(RTCGA.RPPA)
expressionsTCGA(ACC.RPPA, BLCA.RPPA, BRCA.RPPA,
		extract.cols = c("4E-BP1_pS65", "4E-BP1")) %>%
	rename(cohort = dataset) %>%
	select(-bcr_patient_barcode) %>%
	gather(cohort) -> data2plot
names(data2plot)[2] <- "RPPA"
data2plot %>%
	ggplot(aes(fill = cohort, 
						 y = value,
						 x = RPPA)) +
	geom_boxplot() +
	theme_dark(base_size = 15) +
	scale_fill_manual(values = c("#eb6420", "#207de5", "#fbca04")) +
	coord_flip() +
	theme(legend.position = "top") +
	geom_jitter(alpha = 0.5, col = "white", size = 0.6, width = 0.7)



## miRNASeq expressions 
library(RTCGA.miRNASeq)
# miRNASeq has bcr_patienct_barcode in rownames...
mutate(ACC.miRNASeq, 
   bcr_patient_barcode = substr(rownames(ACC.miRNASeq), 1, 25)) -> ACC.miRNASeq.bcr
mutate(CESC.miRNASeq, 
   bcr_patient_barcode = substr(rownames(CESC.miRNASeq), 1, 25)) -> CESC.miRNASeq.bcr
mutate(CHOL.miRNASeq, 
   bcr_patient_barcode = substr(rownames(CHOL.miRNASeq), 1, 25)) -> CHOL.miRNASeq.bcr
mutate(LAML.miRNASeq, 
   bcr_patient_barcode = substr(rownames(LAML.miRNASeq), 1, 25)) -> LAML.miRNASeq.bcr
mutate(PAAD.miRNASeq, 
   bcr_patient_barcode = substr(rownames(PAAD.miRNASeq), 1, 25)) -> PAAD.miRNASeq.bcr
mutate(THYM.miRNASeq, 
   bcr_patient_barcode = substr(rownames(THYM.miRNASeq), 1, 25)) -> THYM.miRNASeq.bcr
mutate(LGG.miRNASeq, 
   bcr_patient_barcode = substr(rownames(LGG.miRNASeq), 1, 25)) -> LGG.miRNASeq.bcr
mutate(STAD.miRNASeq, 
   bcr_patient_barcode = substr(rownames(STAD.miRNASeq), 1, 25)) -> STAD.miRNASeq.bcr


expressionsTCGA(ACC.miRNASeq.bcr, CESC.miRNASeq.bcr, CHOL.miRNASeq.bcr, 
 					 LAML.miRNASeq.bcr, PAAD.miRNASeq.bcr, THYM.miRNASeq.bcr,
 					 LGG.miRNASeq.bcr, STAD.miRNASeq.bcr,
 extract.cols = c("machine", "hsa-mir-101-1", "miRNA_ID")) %>%
							 rename(cohort = dataset) %>%
	filter(miRNA_ID == "read_count") %>%
	select(-bcr_patient_barcode, -miRNA_ID) %>%
	gather(cohort, machine) -> data2plot
names(data2plot)[3:4] <- c("drop","value")
data2plot %>%
	select(-drop) %>%
	mutate(value = as.numeric(value)) %>%
	ggplot(aes(x = cohort,
						 y = log1p(value),
						 fill = as.factor(machine)) )+
	geom_boxplot() +
theme_RTCGA(base_size = 13) +
	coord_flip() +
	theme(legend.position = "top") +
	scale_fill_brewer(palette = "Paired") +
	ggtitle("hsa-mir-101-1")