CalciOMatic-package {CalciOMatic} | R Documentation |
Simulate and analyse calcium imaging data obtained with ratiometric dyes. The package provides tools to fit parametric models of calcium dynamics on experimental data. Two methods are available: the classical 'ratiometric' method and a new 'direct' method, which does not imply any data ratioing and fits directly the fluorescence transients recorded at two excitation wavelengths. The latter method allows for the construction of meaningful confidence intervals on the calcium dynamics parameters.
Package: | CalciOMatic |
Type: | Package |
Version: | 1.1-3 |
Date: | 2009-10-06 |
License: | GPL (>= 2) |
Depends: | cobs |
Sebastien Joucla, Christophe Pouzat
Maintainer: Sebastien Joucla <sebastien.joucla@parisdescartes.fr>
Joucla S, Pippow A, Kloppenburg P and Pouzat C (2009) Quantitative estimation of calcium dynamics from ratiometric measurements: A direct, non-ratioing, approach. J Neurophyiol, in revision
## Load the data set from cockroach olfactory interneurons data(inVitro) ## Define the calibrated parameters of the calcium indicator (Fura-2) R_min <- list(value=0.136, mean=0.136, se=0.00363, USE_se=TRUE) R_max <- list(value=2.701, mean=2.701, se=0.151, USE_se=TRUE) K_eff <- list(value=3.637, mean=3.637, se=0.729, USE_se=TRUE) K_d <- list(value=0.583, mean=0.583, se=0.123, USE_se=TRUE) ## Characteristics of the CCD camera, obtained from 'calibration' experiments G <- 0.146 s_ro <- 16.4 ## Create the data.frame containing the physiological data: physioData <- ratioExpPhysio(dataset="inVitro", expe=2, stim=2, idxOn=10, R_min=R_min, R_max=R_max, K_eff=K_eff, K_d=K_d, G=G, s_ro=s_ro, alphamethod=TRUE) ## Fit the physiological data with the direct method: physioDirectFit <- directFit(physioData, transients=2, SQRT=TRUE, type="mono", AfterPeak=14) ## Plot the raw and fitted data, as well as plots of goodness of fit plot(physioDirectFit, numTransient=2, items=1:6)