Fit a non-parametric mixture model from all identified substitutions

Share:

Description

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

Usage

1
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

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
## 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 )

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.