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Last data update: 2014.03.03

R: Identify the interval of relative substitution frequencies...

getExpInterval

R Documentation

Identify the interval of relative substitution frequencies dominated by experimental induction.

Description

Identifies the interval/support of relative substitution frequencies (RSFs) dominated by the second model component, i.e. by the probability of being induced by the experimental procedure. In addition, this function can be used to generate diagnostic plots of the model fit, representing (i) model densities and log odds ratio (ii) the posterior class probability, i.e. the probability of a given observation being generated by experimental induction.

Usage

getExpInterval(model, bayes = TRUE, leftProb, rightProb, plot = TRUE)

Arguments

`model`	A list containing the model as returned by the function `fitMixtureModel`
`bayes`	Logical, if TRUE the Bayes classifier (cutoff at posterior class probabilities >= 0.5) is applied. If FALSE, custom cutoff values should be provided through leftProb and rightProb. Default is TRUE.
`leftProb`	Numeric, the posterior probability corresponding to the left boundary (start) of the high confidence RSF interval.
`rightProb`	Numeric, the posterior probability corresponding to the right boundary (end) of the high confidence RSF interval.
`plot`	Logical, if TRUE diagnostics plot showing the model components, log odds and the computed posterior with highlighted identified RSF interval are returned.

Value

A list with two numeric slots, corresponding to the extremes of the RSF interval (RSF support).

`supportStart`	start of the high confidence RSF interval
`supportEnd`	end of the high confidence RSF interval

Author(s)

Federico Comoglio and Cem Sievers

References

Sievers C, Schlumpf T, Sawarkar R, Comoglio F and Paro R. (2012) Mixture models and wavelet transforms reveal high confidence RNA-protein interaction sites in MOV10 PAR-CLIP data, Nucleic Acids Res. 40(20):e160. doi: 10.1093/nar/gks697

Comoglio F, Sievers C and Paro R (2015) Sensitive and highly resolved identification of RNA-protein interaction sites in PAR-CLIP data, BMC Bioinformatics 16, 32.

Examples


data( model )

#default
support <- getExpInterval( model = model, bayes = TRUE, plot = TRUE )
support

#custom interval (based, e.g. on visual inspection of posterior class probability 
# or evaluation of FDR using the estimateFDRF function)
support <- getExpInterval( model = model, leftProb = 0.2, rightProb = 0.7, plot = TRUE )
support

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(wavClusteR)
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
Loading required package: Rsamtools
Loading required package: Biostrings
Loading required package: XVector
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/wavClusteR/getExpInterval.Rd_%03d_medium.png", width=480, height=480)
> ### Name: getExpInterval
> ### Title: Identify the interval of relative substitution frequencies
> ###   dominated by experimental induction.
> ### Aliases: getExpInterval
> ### Keywords: core graphics
> 
> ### ** Examples
> 
> 
> data( model )
> 
> #default
> support <- getExpInterval( model = model, bayes = TRUE, plot = TRUE )
> support
$supportStart
[1] 0.007

$supportEnd
[1] 0.98

> 
> #custom interval (based, e.g. on visual inspection of posterior class probability 
> # or evaluation of FDR using the estimateFDRF function)
> support <- getExpInterval( model = model, leftProb = 0.2, rightProb = 0.7, plot = TRUE )
> support
$supportStart
[1] 0.007

$supportEnd
[1] 0.98

> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>