mitoODE (version 1.10.0)

mitoODE: Dynamical modelling of phenotypes in a genome-wide RNAi live-cell imaging assay

Description

The mitoODE package implements the differential model fitting used in the ``Dynamical modelling of phenotypes in a genome-wide RNAi live-cell imaging assay'' paper and includes the code to reproduce the presented figures and results. See the vignette for details about the model.

Usage

getp0(y, p0=NULL, sd=0)
fitmodel(y, p0, pconst, nfits=1, sd=0, mc.cores=1, best=TRUE)

Arguments

y

A matrix with 4 columns containing the cell count time series, such as the one returned by readspot.

p0

A vector of 10 numeric parameters, such as returned by getp0, containing the initial conditions. See the vignette for details.

pconst

A vector of 10 numeric parameters, containing g.kim, g.kmi, g.mit0 and p.lambda. See the vignette for details.

nfits

The number of fits to be done. Default is 1.

sd

A numeric indicating the standard deviation of some Gaussian noise added to the initial conditions before fitting. Default is 0.

mc.cores

A numeric indicating how many parallel cores should be used to fit the cell count time series. Default is 1.

best

A logical. See return value.

Value

getp0 returns a vector of 10 parameters that can be used as initial conditions. If TRUE, fitmodel returns the best fitted parameters, otherwise returns the all n fitted parameters.

Details

The function fitmodel fits the cell count data to the differential equation model described in the vignette, using the penalized Levenberg-Marquardt nls.lm algorithm.

See Also

loadFittedData, figure1, plotfit

Examples

 ## read spot
 spotid <- 1000
 y <- readspot(spotid)

 ## fit data
 pconst <- c(g.kim=0.025, g.kmi=0.57, g.mit0=0.05, p.lambda=4)
 p0 <- getp0()
 pp <- fitmodel(y, p0, pconst)
 round(pp, 2)

 ## plot fitted data
 plotfit(spotid, pp)