Model3: Fit and Plot intensities
In Rolexa: Statistical analysis of Solexa sequencing data

Description Usage Arguments Details Value Author(s) References Examples

Model-based classification of intensity data points, to either perform a base calling or generate diagnostic plots

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## S4 method for signature 'RolexaRun'
SeqScore(run=Rolexa.env,int,seqInit,colonies,cycles,plot=FALSE)
SeqScore(run,...)

`run`	a `RolexaRun` object defining the run parameters
`int`	a `SolexaIntensity` object
`seqInit`	a `ShortRead` object
`colonies`	which colonies to select
`cycles`	which cycles to select
`plot`	if TRUE do a plot rather then perform a base-calling
`...`	additional arguments, ignored

This will use the EEV model of mclust to fit the data clouds with a mixture of 4 gaussian distributions. and generate a list of tags and entropy scores for each sequenced colony (if plot is FALSE) or plots two 2-dimensional projections for each selected cycle with gaussian parameters represented by standard ellipses and data points colored according to the induced classification.

If fit is TRUE, then the EM algorithm is run to convergencce, otherwise only an E-step and an M-step are performed to evaluate the probabilities.

The fitting procedure then uses HThresholds to decide if a base is unambiguous and if degenerate IUPAC codes will be used.

if plot is FALSE, SeqScore returns a list with an id slot containing the colonies coordinates, an sread slot which is a DNAStringSet object and an entropy matrix

Jacques Rougemont, Arnaud Amzallag, Christian Iseli, Laurent Farinelli, Ioannis Xenarios, Felix Naef

Probabilistic base calling of Solexa sequencing data, BMC Bioinformatics 2008, 9:431

path = SolexaPath(system.file("extdata", package="ShortRead"))
rolenv = SetModel(idsep="_")
int = readIntensities(path,pattern="s_1_0001",withVariability=FALSE)
seq = CombineReads(run=rolenv,path=path,pattern="s_1_0001_seq*")
results = SeqScore(run=rolenv,int=int,seqInit=seq,cycles=1:10)
results$sread