Nothing
## ----warning=FALSE, message=FALSE, tidy=TRUE-----------------------------
library("VSE")
bca.ld <- loadLd(file.path(system.file("extdata",
"ld_BCa_raggr.csv",
package="VSE")),
type="raggr")
#bca.ld is a GRanges object
bca.ld
## ----warning=FALSE, message=FALSE, tidy=TRUE, fig.height=5, fig.cap="LD Sizes of BCa AVS"----
bca.avs <- makeAVS(bca.ld)
#Check the size of each LD block
avs.size <- avsSize(bca.avs)
head(avs.size)
library(ggplot2)
ggplot(avs.size, aes(x=tagID, y=Size)) +
geom_bar(stat="identity") +
coord_flip() +
theme_classic() +
theme(axis.text.y = element_text(size=5))
## ----warning=FALSE, message=FALSE, tidy=TRUE-----------------------------
bca.avs
## ----warning=FALSE, message=FALSE, tidy=TRUE-----------------------------
# Load MRVS
load(file.path(system.file("extdata",
"bca.mrvs.200.Rda",
package="VSE")))
class(bca.mrvs.200)
## ----warning=FALSE, message=FALSE, tidy=TRUE-----------------------------
#Downloading sample regions
sampleSheet_path <- loadSampleRegions()
#Loading sample sheet
samples <- read.csv(sampleSheet_path, header=TRUE)
samples
## ----warning=FALSE, message=FALSE, tidy=TRUE, fig.height=5, fig.width=5----
bca.intersect <- intersectMatrix(bca.avs,
regions=samples,
col=c("white","grey10"),
scale="none",
margins=c(5,5),
cexRow = 1,
cexCol = 0.5,
Rowv=NA,
Colv=NA)
bca.intersect
## ----warning=FALSE, message=FALSE, tidy=TRUE-----------------------------
bca.vse <- variantSetEnrichment(bca.avs, bca.mrvs.200, samples)
## ----warning=FALSE, message=FALSE, tidy=TRUE, fig.height=7, fig.width=7, fig.cap="QQ plot of null distribution across all genomic features"----
par.original <- par(no.readonly=TRUE);
par(mfrow=c(ceiling(length(samples$Peaks)/3), 3),
mai=c(1,1,0.5,0.1))
VSEqq(bca.vse)
par(par.original)
## ----warning=FALSE, message=FALSE, tidy=TRUE-----------------------------
bca.vse.res <- VSESummary(bca.vse)
bca.vse.res
## ----warning=FALSE, message=FALSE, tidy=TRUE, fig.cap="VSE analysis of BCa AVS across 6 genomic features. The points in red denotes significantly enriched region (Bonferroni adjusted P-value < 0.01)"----
VSEplot(bca.vse,
las=2,
pch=20,
cex=1,
cex.main=0.6,
padj = 0.05,
main="BCa AVS in MCF7 genomic features")
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