gRxSummary

Description

Summarize gRxCluster Results

Usage

gRxSummary(object, targetFD = NULL)

Arguments

Details

Get the FDR and related data for a run of gRxCluster. By selecting a value for targetFD that is smaller that what was used in constructing the object, fewer clumps will be included in the computation fo the False Discovery Rate - akin to what would have been obtained from the object if it had been constructed using that value.

Value

a list containing the summarized results

Author(s)

Charles Berry

Examples

x.seqnames <- rep(letters[1:3],each=50)
x.starts <- c(seq(1,length=50),seq(1,by=2,length=50),seq(1,by=3,length=50))
x.lens <- rep(c(5,10,15,20,25),each=2)
x.group <- rep(rep(c(TRUE,FALSE),length=length(x.lens)),x.lens)
x.kvals <- as.integer(sort(unique(x.lens)))
x.res <- gRxCluster(x.seqnames,x.starts,x.group,x.kvals,nperm=100L)
gRxSummary(x.res)
rm( x.seqnames, x.starts, x.lens, x.group, x.kvals, x.res)

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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> library(geneRxCluster)
Loading required package: GenomicRanges
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

Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

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

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: GenomeInfoDb
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/geneRxCluster/gRxSummary.Rd_%03d_medium.png", width=480, height=480)
> ### Name: gRxSummary
> ### Title: gRxSummary
> ### Aliases: gRxSummary
> 
> ### ** Examples
> 
> x.seqnames <- rep(letters[1:3],each=50)
> x.starts <- c(seq(1,length=50),seq(1,by=2,length=50),seq(1,by=3,length=50))
> x.lens <- rep(c(5,10,15,20,25),each=2)
> x.group <- rep(rep(c(TRUE,FALSE),length=length(x.lens)),x.lens)
> x.kvals <- as.integer(sort(unique(x.lens)))
> x.res <- gRxCluster(x.seqnames,x.starts,x.group,x.kvals,nperm=100L)
> gRxSummary(x.res)
$Clusters_Discovered
[1] 4

$FDR
[1] 0.156

$permutations
[1] 100

$targetFD
[1] 5

$call
gRxCluster(object = x.seqnames, starts = x.starts, group = x.group, 
    kvals = x.kvals, nperm = 100L, cutpt.tail.expr = critVal.target(k, 
        n, target = 5, posdiff = x), cutpt.filter.expr = as.double(apply(x, 
        2, median, na.rm = TRUE)))

> rm( x.seqnames, x.starts, x.lens, x.group, x.kvals, x.res)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>