R: Estimation of binding site positions

pics {PICS}

R Documentation

Estimation of binding site positions

Description

This object contains Estimation of binding site positions and has the following slots: segReadsList, dataType.

Usage

PICS(segReadsList,dataType=NULL, paraEM=NULL, paraPrior=NULL, nCores=1)

Arguments

`segReadsList`	This object contains segmentation of Genome
`dataType`	The type of data you are processing: specified ‘TF’ for transcription factor.
`paraEM`	A list of parameters for the EM algorithm as returned by the `setParaEm` function. The default parameters should be good enough for most usages.

: minK: an integer, default=1. The minimum number of binding events per region. If the value is 0, the minimum number is automatically calculated.
: maxK: an integer, default=15. The maximum number of binding events per region. If the value is 0, the maximum number is automatically calculated.
: tol: a numeric, default=1e-4. The tolerance for the EM algorithm.
: B: an integer, default=100. The maximum number of iterations to be used.
: mSelect: a character string specifying the information criteria to be used when selecting the number of binding events. Default="BIC"
: mergePeaks: a logical stating whether overlapping binding events should be picked. Default=TRUE
: mapCorrect: a logical stating whether mappability profiles should be incorporated in the estimation, i.e: missing reads estimated. Default=TRUE

paraPrior

A list of parameters for the prior distribution as returned by the setParaPrior function. The default parameters should be good enough for most usages.

: xi: an integer, default=200. The average DNA fragment size.
: rho: an integer, default=1. A variance parameter for the average DNA fragment size distribution.
: alpha: an integer, default=20. First hyperparameter of the inverse Gamma distribution for sigma^2 in the PICS model
: beta: an integer, default=40000. Second hyperparameter of the inverse Gamma distribution for sigma^2 in the PING model
: lambda: an integer, default=0. The precision of the prior for mu used for histone data.
: dMu: an integer, default=0. Our best guess for the distance between two neighboring nucleosomes.

nCores

An integer. The number of cores that should be used in parallel by the function.

Methods

code: signature(x = ``pics''): return the error code for each list element (i.e. candidate region) of a PICS object. If the string is empty, there were no errors.
plot: signature(x = ``pics''): Plot all regions in the PICS object. This might be long, and should only be used to plot a few regions, so subset the object before plotting.
sigmaSqR: signature(x = ``pics''): return the variance parameter of the reverse (R) distribution for each binding event.
sigmaSqF: signature(x = ``pics''): return the variance parameter of the forward (F) distribution for each binding event.
score: signature(x = ``pics''): return the score for each binding event.
scoreF: signature(x = ``pics''): return the score of the forward (F) for each binding event.
scoreR: signature(x = ``pics''): return the score of the forward (R) for each binding event.
maxRange: signature(x = ``pics''): return the range maximum.
minRange: signature(x = ``pics''): return the range minimal.
K: signature(x = ``pics''): subset PICS object.
wigDensity: signature(x = ``pics''): return the density for each binding event.

Author(s)

Xuekui Zhang, Arnaud Droit <arnaud.droit@crchuq.ualaval.ca> and Raphael Gottardo <rgottard@fhcrc.org>

References

X. Zhang, G. Robertson, M. Krzywinski, K. Ning, A. Droit, S. Jones, and R. Gottardo, “PICS: Probabilistic Inference for ChIP-seq” arXiv, 0903.3206, 2009. To appear in Biometrics.