Histograms of all pairwise sample correlations, showing identified doppelgangers.

Description

Identified doppelgangers are shown with a red vertical line overlaid on a histogram of pairwise sample correlations. One plot is made per pair of datasets.

Arguments

x

An object of class DoppelGang

skip.no.doppels

(default FALSE) If TRUE, do not plot histograms where no doppelgangers were identified.

plot.pair

An optional character vector of length two, providing the names of two datasets. If provided, only the comparison of these two datasets will be plotted.

...

Additional arguments passed on to hist.

Value

None

Methods

signature(x = "DoppelGang")

Histograms of all pairwise sample correlations, showing identified doppelgangers.

Author(s)

Levi Waldron

Examples

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library(curatedOvarianData)
data(TCGA_eset)
data(GSE26712_eset)
## Remove some TCGA samples to speed computation:
keep.tcga <-
c("TCGA.13.2060", "TCGA.24.2290", "TCGA.25.2392", "TCGA.25.2404",
"TCGA.59.2349", "TCGA.09.2044", "TCGA.24.2262", "TCGA.24.2293",
"TCGA.25.2393", "TCGA.25.2408", "TCGA.59.2350", "TCGA.09.2045",
"TCGA.24.2267", "TCGA.59.2351", "TCGA.09.2048", "TCGA.24.2271",
"TCGA.24.2298", "TCGA.25.2398", "TCGA.59.2354", "TCGA.09.2050",
"TCGA.24.2281", "TCGA.09.2051", "TCGA.29.2428", "TCGA.09.2055",
"TCGA.24.2289", "TCGA.29.2414", "TCGA.59.2352", "TCGA.36.2532",
"TCGA.36.2529", "TCGA.36.2551", "TCGA.42.2590", "TCGA.13.2071",
"TCGA.29.2432", "TCGA.36.2537", "TCGA.36.2547", "TCGA.04.1369",
"TCGA.42.2591", "TCGA.23.2641", "TCGA.29.2434", "TCGA.36.2538",
"TCGA.36.2548", "TCGA.04.1516", "TCGA.42.2593", "TCGA.36.2549",
"TCGA.04.1644", "TCGA.13.2057", "TCGA.23.2647", "TCGA.36.2530",
"TCGA.36.2552", "TCGA.42.2587", "TCGA.13.2061", "TCGA.42.2588",
"TCGA.36.2544", "TCGA.42.2589", "TCGA.13.2066", "TCGA.61.2613",
"TCGA.61.2614", "TCGA.24.1852", "TCGA.29.1704", "TCGA.13.1819"
)
keep.tcga <- unique(c(keep.tcga, sampleNames(TCGA_eset)[1:200]))
testesets <- list(Bonome08=GSE26712_eset, TCGA=TCGA_eset[, keep.tcga])
results1 <- doppelgangR(testesets,
                        corFinder.args=list(use.ComBat=FALSE), phenoFinder.args=NULL, cache.dir=NULL)
plot(results1)