This function has not been properly implemented yet

Description

Method to find the cutoff at which gains and losses are considered significant using permutations

Usage

findSigLevelFdr(data, observedSpm, n = 1, fdrTarget=0.05, maxmem=1000)

Arguments

Details

The number of permutations needed for reliable results depends on the data and can not be determined beforehand. As a general rule-of-thumb around 100 permutations should be used for 'quick checks' and around 2000 permutations for more rigorous testing. The FDR method is less conservatie than the p-value based approach since instead of controlling the family wise error rate (FWER, P(false positive > 1)) it controls the false discovery rate (FDR) (false positives / total number of called data points).

Value

A list with the cutoffs corresponding to the given FDR

Author(s)

Jorma de Ronde

See Also

plotScaleSpace

Examples

data(hsSampleData)
data(hsMirrorLocs)

spm1mb <- calcSpm(hsSampleData, hsMirrorLocs)

sigLevel1mb <- findSigLevelTrad(hsSampleData, spm1mb, n=3)

plot(spm1mb, sigLevels=sigLevel1mb)
plotScaleSpace(list(spm1mb), list(sigLevel1mb), type='g')

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 '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.
Type 'q()' to quit R.

> library(KCsmart)
Loading required package: siggenes
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: multtest
Loading required package: splines
Loading required package: KernSmooth
KernSmooth 2.23 loaded
Copyright M. P. Wand 1997-2009
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/KCsmart/findSigLevelFdr.Rd_%03d_medium.png", width=480, height=480)
> ### Name: findSigLevelFdr
> ### Title: This function has not been properly implemented yet
> ### Aliases: findSigLevelFdr
> ### Keywords: manip
> 
> ### ** Examples
> 
> data(hsSampleData)
> data(hsMirrorLocs)
> 
> spm1mb <- calcSpm(hsSampleData, hsMirrorLocs)
[1] "Mirror locations looking fine"
[1] "Splitting data .."
[1] "Summing data .."
[1] "Mirroring data .."
[1] "Calculating sample point matrix .."

Processing chromosome 1 

Processing chromosome 10 

Processing chromosome 11 

Processing chromosome 12 

Processing chromosome 13 

Processing chromosome 14 

Processing chromosome 15 

Processing chromosome 16 

Processing chromosome 17 

Processing chromosome 18 

Processing chromosome 19 

Processing chromosome 2 

Processing chromosome 20 

Processing chromosome 21 

Processing chromosome 22 

Processing chromosome 3 

Processing chromosome 4 

Processing chromosome 5 

Processing chromosome 6 

Processing chromosome 7 

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Processing chromosome X 

Processing chromosome Y 


[1] "Done"
> 
> sigLevel1mb <- findSigLevelTrad(hsSampleData, spm1mb, n=3)
[1] "Calculating alpha =  0.05 significance cut-off"
[1] "Found  584  pos peaks and  598  neg peaks in observed sample point matrix"
[1] "Calculating Mirror Positions"
[1] "Starting permutations .."
 At iteration 1 of 3[1] "Permuting"
[1] "Combining"
[1] "Returning"
 At iteration 2 of 3[1] "Permuting"
[1] "Combining"
[1] "Returning"
 At iteration 3 of 3[1] "Permuting"
[1] "Combining"
[1] "Returning"

> 
> plot(spm1mb, sigLevels=sigLevel1mb)
> plotScaleSpace(list(spm1mb), list(sigLevel1mb), type='g')
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>