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

Value

None

Methods

signature(x = "DoppelGang")

Histograms of all pairwise sample correlations, showing identified doppelgangers.

Author(s)

Levi Waldron

Examples

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)

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)

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Type 'license()' or 'licence()' for distribution details.

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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.
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> library(doppelgangR)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

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

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

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

    IQR, mad, xtabs

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

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: BiocParallel
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/doppelgangR/plot-methods.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot-methods
> ### Title: Histograms of all pairwise sample correlations, showing
> ###   identified doppelgangers.
> ### Aliases: plot-methods plot,DoppelGang plot,DoppelGang-method
> ###   plot,DoppelGang,ANY-method plot.DoppelGang plot.doppelgangR
> ### Keywords: methods
> 
> ### ** Examples
> 
> library(curatedOvarianData)
Loading required package: affy
> 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)
Working on datasets Bonome08 and Bonome08
Calculating correlations...
Identifying correlation doppelgangers...
Working on datasets TCGA and TCGA
Calculating correlations...
Identifying correlation doppelgangers...
Working on datasets Bonome08 and TCGA
Calculating correlations...
Identifying correlation doppelgangers...
Finalizing...
> plot(results1)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>