Last data update: 2014.03.03

 R: Gather Expressions for TCGA Datasets
expressionsTCGAR Documentation

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.

Note

Input data.frames should contain column bcr_patient_barcode if extract.cols is specified.

Author(s)

Marcin Kosinski, m.p.kosinski@gmail.com

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")

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(RTCGA)
Welcome to the RTCGA (version: 1.2.2).
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/RTCGA/expressionsTCGA.Rd_%03d_medium.png", width=480, height=480)
> ### Name: expressionsTCGA
> ### Title: Gather Expressions for TCGA Datasets
> ### Aliases: expressionsTCGA
> 
> ### ** Examples
> 
> 
> ## for all examples
> library(dplyr)

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

> 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")
Scale for 'fill' is already present. Adding another scale for 'fill', which
will replace the existing scale.
> 	
> ## 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")
Scale for 'fill' is already present. Adding another scale for 'fill', which
will replace the existing scale.
Warning message:
Removed 2 rows containing non-finite values (stat_boxplot). 
> 
> 
> ## 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")
Scale for 'fill' is already present. Adding another scale for 'fill', which
will replace the existing scale.
> 
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>


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