mitoODE: Dynamical modelling of phenotypes in a genome-wide RNAi...

In mitoODE: Implementation of the differential equation model described in "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.

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.

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.

Author(s)

Gregoire Pau, [e-mail], 2012

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)

mitoODE documentation built on Aug. 12, 2020, 2 a.m.