ctb: CellTiter-Blue Cell Viability Assay Data

In daniel-gerhard/medrc: Mixed effect dose-response curves

Description

Neurotoxicity test using the CellTiter-Blue Cell Viability Assay on SH-SY5Y cells for increasing concentrations of acrylamide.

Usage

data(ctb)

Format

A data frame with 647 observations on the following 5 variables.

well

well ID of a 96 well plate

conc

12 concentrations of acrylamide, ranging from 0-500mM

fluorescence

measured fluorescence after adding the resazurin reagent into the wells

day

integer denoting 3 different days

plate

factor with 7 levels representing the plate ID

References

Frimat, JP, Sisnaiske, J, Subbiah, S, Menne, H, Godoy, P, Lampen, P, Leist, M, Franzke, J, Hengstler, JG, van Thriel, C, West, J. The network formation assay: a spatially standardized neurite outgrowth analytical display for neurotoxicity screening. Lab Chip 2010; 10:701-709.

Examples

## Not run: 
data(ctb)
ctb$day <- as.factor(ctb$day)
ctb$dayplate <- as.factor(with(ctb, paste(day, plate, sep="/")))

ggplot(ctb, aes(x=log(conc), y=fluorescence, colour=day, group=day:plate)) + 
  geom_point()

# starting values for fixed effects
fix <- coefficients(drm(fluorescence ~ conc, fct=LL.4(), data=ctb))

# starting values for random day effects
rday <- drm(fluorescence ~ conc, curveid=day, fct=LL.4(), data=ctb)
cmatday <- matrix(coefficients(rday), ncol=4)
mday <- apply(cmatday, 2, mean)
names(mday) <- letters[2:5]
rmatday <- t(apply(cmatday, 1, function(x) x-mday))
rownames(rmatday) <- levels(ctb$day)
colnames(rmatday) <- letters[2:5]

start <- list(fixed=fix, random=list(day=rmatday[,3, drop=FALSE]))


## set of nonlinear mixed models
ctb.LL4.mixed <- medrm(fluorescence  ~ conc, fct=LL.4(), 
                       data=ctb, random=d  ~ 1 | day/plate, start=start)
ctb.LN4.mixed <- medrm(fluorescence  ~ conc, fct=LN.4(), 
                       data=ctb, random=d  ~ 1 | day/plate, start=start)
ctb.W14.mixed <- medrm(fluorescence  ~ conc, fct=W1.4(), 
                       data=ctb, random=d  ~ 1 | day/plate, start=start)
ctb.W24.mixed <- medrm(fluorescence  ~ conc, fct=W2.4(), 
                       data=ctb, random=d  ~ 1 | day/plate, start=start)
ctb.FPL4b.mixed <- medrm(fluorescence ~ conc, fct=FPL.4(-1, 1), 
                         data=ctb, random=d ~ 1 | day/plate, start=start)
ctb.FPL4c.mixed <- medrm(fluorescence ~ conc, fct=FPL.4(-1, 2), 
                         data=ctb, random=d  ~ 1 | day/plate, start=start)
ctb.FPL4d.mixed <- medrm(fluorescence ~ conc, fct=FPL.4(-0.5, 3), 
                         data=ctb, random=d  ~ 1 | day/plate, start=start)

## information criteria
AIC(ctb.LL4.mixed, ctb.LN4.mixed, ctb.W14.mixed,
    ctb.W24.mixed, ctb.FPL4b.mixed,
    ctb.FPL4c.mixed, ctb.FPL4d.mixed)



## End(Not run)

daniel-gerhard/medrc documentation built on May 14, 2019, 3:38 p.m.