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library(MultiAssayExperiment)
library(ggplot2)
library(scales)
if(!file.exists("coadMAEO.rds")){
download.file("http://s3.amazonaws.com/multiassayexperiments/coadMAEO.rds",
destfile="coadMAEO.rds")
}
if(!file.exists("brcaMAEO.rds")){
download.file("http://s3.amazonaws.com/multiassayexperiments/brcaMAEO.rds",
destfile="brcaMAEO.rds")
}
coad <- readRDS("coadMAEO.rds")
brca <- readRDS("brcaMAEO.rds")
fun <- function(mae){
mae <- mae[, , c("Mutations", "gistict")]
mae <- mae[, !rownames(colData(mae)) %in% names(duplicated(mae)$Mutations), ]
mae <- mae[, complete.cases(mae), ]
mae$nummuts <- sapply(experiments(mae)$Mutations, length) / 50
mae$cnload <- colMeans(abs(assay(mae[, , "gistict"])[[1]]))
res <- cbind(mae$nummuts, mae$cnload)
colnames(res) <- c("N of Mutations", "SCNA level")
res <- data.frame(res)
fit <- lm(SCNA.level ~ log10(N.of.Mutations), data=res)
res$predictions = predict(fit)
output <- list(res=res, fit=fit)
return(output)
}
cores <- fun(coad)
brres <- fun(brca)
allRes <- rbind(
cbind(Cancer="Colon Adenocarcinoma", cores$res),
cbind(Cancer="Breast", brres$res))
cbPalette <- c("#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
png("scna.png", width=4, height=4, units="in", res=600)
ggplot(allRes, aes(N.of.Mutations, SCNA.level, color=Cancer))+
geom_point()+
scale_x_continuous(trans = log2_trans(), limits=c(0.2,NA),
breaks = trans_breaks("log2", function(x) 2^x))+
geom_smooth(method='lm')+
theme_classic(15)+
xlab("Mutations/Mb")+
ylab("SCNA Score")+
labs(color="")+
theme(legend.position="bottom")+
scale_colour_manual(values=cbPalette)
dev.off()
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