FitMixtureModel: Fit a non-parametric mixture model from all identified...

In FedericoComoglio/wavClusteR: Sensitive and highly resolved identification of RNA-protein interaction sites in PAR-CLIP data

Description

Estimates the two-component mixture model consisting of the mixing coefficients and the density functions.

Usage

fitMixtureModel(countTable, substitution = "TC")

Arguments

countTable	A GRanges object, corresponding to a count table as returned by the getAllSub function
substitution	A character indicating which substitution is induced by the experimental procedure (e.g. 4-SU treatment - a standard in PAR-CLIP experiments - induces T to C transitions and hence substitution = 'TC' in this case.)

Value

A list containing:

l1	The first mixing coefficient
l2	The second mixing coefficient
p	The mixture model
p1	The first component of the mixture
p2	The second component of the mixture

Author(s)

Federico Comoglio and Cem Sievers

See Also

getAllSub getExpInterval

Examples

## Not run: 
filename <- system.file( "extdata", "example.bam", package = "wavClusteR" )
example <- readSortedBam(filename = filename)
countTable <- getAllSub( example, minCov = 10, cores = 1 )

fitMixtureModel( countTable, substitution = "TC" )

## End(Not run)

#load and inspect the model
data( model )
str( model )

#plot densities and estimate the relative substitution frequency support dominated by PAR-CLIP induction
getExpInterval( model, bayes = TRUE, plot = TRUE )

FedericoComoglio/wavClusteR documentation built on Oct. 29, 2020, 2:44 p.m.