smoothExp: smooth gene expression trajectories in an ExpressionSet, using a phenoData variable as the domain

Description

smooth gene expression trajectories in an ExpressionSet, using a phenoData variable as the domain

Usage

smoothExp(eset, phenovar, keepAt = NULL, fitter = mgcv::gam,
                 fmla = y ~ s(x, k = 9, fx = TRUE), retain =
                 c("gcv.ubre", "sig2", "coefficients"), igran = 50,
                 exclind = NULL, dogcv.locfit = FALSE, maxna = 5, pv =
                 varfitRanpart(fitter, fmla))
smoothExpFull(eset, phenovar, fitter, fmla=y ~ s(x, k = 9, fx=TRUE))

Arguments

eset

instance of ExpressionSet

phenovar

string naming a phenoData variable in eset that will serve as the domain of the expression trajectory function

keepAt

sequence of values of domain variable at which fitted values are to be computed and saved

fitter

R function that will fit a model given a formula as supplied in fmla

fmla

A formula object that will serve as a template; variable y is bound to expression values, and x is bound to domain values

retain

names of extra components of the fitted model object to be extracted and saved

igran

granularity of the iteration count report (string emitted if options()$verbose is TRUE

dogcv.locfit

set to TRUE to obtain the locfit gcv estimate

exclind

if pv is varpredFIX a fixed set of test point indices is specified in this vector; leave NULL otherwise

maxna

numeric threshold, maximum number of NA values of expression permitted; if there are more, the gene is skipped

predictive variance plugin -- accepts a closure

Value

a list with one element per gene with components origx, origy, newx, preds and extras for the retain components, and locfit.gcv if dogcv.locfit is set.

Details

This function iterates over all features in an ExpressionSet instance, fitting smooth models for expression as a function of some phenodata variable, typically a time measure. The objective is to support a ``drop-in'' interface, so that alternate smoothing technologies may be incorporated.

Examples

Run this code

data(yccalp)
okp = options()
options(verbose=TRUE)
dem = smoothExp( yccalp[1:20,], "minutes", keepAt=seq(0,120,5), igran=5)
plot(dem[[1]])
dem2 = smoothExp( yccalp[1:20,], "minutes", keepAt=seq(0,120,5),
   fitter=locfit::locfit, fmla=y~lp(x,nn=.4),dogcv.locfit=TRUE, igran=5)
plot(dem2[[1]])
dem3 = smoothExp( yccalp[1:20,], "minutes", keepAt=seq(0,120,5),
   fitter=locfit::locfit, fmla=y~lp(x,nn=.4),dogcv.locfit=FALSE,
   exclind=c(3,6,9,12,15), pv=varfitFIX(locfit::locfit,
   y~lp(x,nn=.4), c(3,6,9,12,15)), igran=5)
plot(dem3[[1]])
pv2 = gcvs(dem2) # get locfit gcv est
pv3 = extract(dem3, "predvar") # use the fixed test points est
ipar = par(no.readonly=TRUE)
par(mfrow=c(2,2))
plot(pv2,pv3)
pv3
bes3 = names(sort(pv3))[1]
plot(dem2[[bes3]], main="full data fit")
plot(dem3[[bes3]], main="leave 5 out fit, x=test point")
par(ipar)

options(okp)

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