wfm.fit: Fit Wfm model to trancriptome data

In waveTiling: Wavelet-Based Models for Tiling Array Transcriptome Analysis

Description

Main function to fit a wavelet-based functional model to the tiling array expression data.

Usage

wfm.fit(object, filter.overlap=NULL, design=c("time","circadian","group","factorial","custom"), n.levels, factor.levels=NULL, chromosome, strand, minPos, maxPos, design.matrix=NULL, var.eps=c("margLik","mad"), prior=c("normal","improper"), eqsmooth=FALSE, max.it=20, wave.filt="haar", skiplevels=NULL, trace=FALSE, save.obs=c("plot","regions","all"))

Arguments

object	object of class WaveTilingFeatureSet
filter.overlap	object of class mapFilterProbe
design	character indicating the design of tiling array experiment. Currently, the following designs are implemented: time for a time-course design based on polynomial contrasts; circadian for circadian rhythm analysis; group for unordered one-factor designs; factorial for two-factor designs; custom for other designs. When using design="custom" a specific design.matrix needs to be given.
n.levels	number of levels in wavelet decomposition (integer)
factor.levels	factor levels in case of two-factor analysis. Vector of integers with length the number of factors in the experiment, and with elements the number of levels for the respective factors.
chromosome	numeric to indicate the chromosome associated with transcriptome data to fit
strand	character to indicate the strand orientation associated with transcriptome data to fit. Either "forward" or "reverse".
minPos	integer to indicate minimum genomic position
maxPos	integer to indicate maximum genomic position
design.matrix	custom design matrix to use
var.eps	character indicating how to estimate residual variance. Either "margLik" for marginal maximum likelihood based estimation or "mad" for estimation based on the MAD (more info see references).
prior	character indicating which prior distribution to put on effect functions. Either "normal" for a normally distributed prior, or "improper" for an improper prior (more info see references).
eqsmooth	logical indicating whether to force equal amount of smooth for different effect functions or not
max.it	integer giving the maximum number of iteration for estimation
wave.filt	character indicating which wavelet filter to use. Default is "haar".
skiplevels	integer indicating how many wavelet levels to put equal to 0
trace	logical indicating whether to trace estimation
save.obs	character to indicate which output to store in return object. Either "plot": all info needed to make the plots or "all": store all possible info.

Value

object of class WfmFit

Author(s)

Kristof De Beuf <[e-mail]>

References

[1] Clement L, De Beuf K, Thas O, Vuylsteke M, Irizarry RA and Crainiceanu CM. (2012) Fast wavelet based functional models for transcriptome analysis with tiling arrays. Statistical Applications in Genetics and Molecular Biology 11: Iss. 1, Article 4.

[2] De Beuf K, Andriankaja, M, Thas O, Inze D, Crainiceanu CM and Clement L (2012) Model-based analysis of tiling array expression studies with flexible designs. Technical document.

Examples

  library(waveTilingData)
  data(leafdevBQ)
  data(leafdevMapAndFilterTAIR9)
  leafdevFit <- wfm.fit(leafdevBQ,filter.overlap=leafdevMapAndFilterTAIR9,design="time",n.levels=10,chromosome=1,strand="forward",minPos=22000000,maxPos=24000000,var.eps="marg",prior="improper",skiplevels=1,save.obs="plot",trace=TRUE)

waveTiling documentation built on Oct. 31, 2019, 9:23 a.m.