ic50: Standardized evaluation of cell-based compound screens
In ic50: Standardized high-throughput evaluation of cell-based compound screens

Description Usage Arguments Details Value Note Author(s) References Examples

Calculation of IC50 values, automatic drawing of dose-response curves and validation of compound screens on 96- and 384-well plates.

ic50.96(files,measure=NULL,control=NULL,dilution=NULL,inhib=NULL,
        normalize="mean",graphics="mean",outdir="./results")
ic50.384(files,measure=NULL,control=NULL,dilution=NULL,inhib=NULL,
         normalize="single",graphics="mean",outdir="./results")

`files`	Character vector of files containing the raw data.
`measure`	Configuration file for the locations of the measurement wells.
`control`	Configuration file for the locations of the control wells.
`dilution`	Configuration file for the concentrations in each measurement. See details below.
`inhib`	Vector of real numbers between 0 and 1 specifying the percentage of inhibition to compute concentrations for. Defaults to 0.5 for all compounds.
`normalize`	Method to normalize the measurement by the controls. For `"mean"`, the mean of the controls specified by `control` is used; `"single"` requires one individual control well per measurement well.
`graphics`	A character specifying the plotting method. For `"mean"`, a dose-response curve of the mean values of the measurement series is given, whereas one curve is plotted for each if `"single"` is specified. For `"fitted"`, a sigmoid-shaped derivation of the logistic model is fitted to the data.
`outdir`	The directory where the results will be written.

In cytotoxicity screens of chemical compounds, biological activity is typically indicated by the concentration for which a particular proportion (typically 0.5) of cell growth is inhibited after a predefined treatment period. For this purpose, all concentrations are plotted against the percentages of cells still being alive under this treatment, forming a dose-response curve under which the preimage of the 0.5 point is defined as the half-maximum inhibitory concentration (IC50). For high-throughput screens (HTS), in particular, the evaluation of the data needs to be performed in an automatic fashion.

The data input for the script is performed by tab-delimited data files which are the typical output from appropriate microplate readers. A character vector of file names is therefore expected as the first argument to the functions. If 96- or 384-well plates are used for the screen, the arrangement of the wells is in principle arbitrary. The design must be specified by three tab-delimited files with one for the coordinates of the measurement wells, one for the control wells and one for the concentrations of the respective compound. Several examples of each of these files are given in the inst folder, e.g. the files "default384_measure.txt", "default384_control.txt" and "default384_dilution.txt". Details on the arrangement of these files are given in the documentation of the corresponding data sets, e.g. for default384_measure. In addition, a tutorial document describing how to prepare the data and configuration is included in the ic50 package.

For each compound in the screen, a graphics output is given in the file "dose_response_curves.pdf" in the output directory, where the screen data are displayed as specified by the argument graphics. In addition, quantitative results are written to a file "ic50.txt" in the same directory. Inhibitory concentrations are calculated for each of the curves and are given together with the respective confidence intervals. The measurement accuracy is evaluated by the maximum of the standard deviations at the respective concentrations and by the coefficient of variation of the concentration values as determined from the single replicates. Finally, the normalized data rows detected from the plates in use are written to the file "measurement.txt", combined in one group for each compound.

Please make use of the tutorial document in the doc folder which helps users to get started with the software.

A data frame with the following variables:

`compound`	Compound names.
`ic50`	The inhibitory concentrations for the respective compounds.
`clow`	Lower 0.95 confidence limits for the IC values.
`cup`	Upper 0.95 confidence limits for the IC values.
`maxsd`	Maximum of the standard deviations at the measured concentrations as determined from the single replicates.
`cv`	Coefficient of variation of the IC values as determined from the single replicates.

The nonlinear regression for the sigmoidal-shaped curve is not performed by the least-squares method. Instead, the parameters are adapted to the data by assumptions on the shape of an "ideal" curve such as location and bending.

Peter Frommolt, University of Cologne peter.frommolt@uni-koeln.de
http://portal.ccg.uni-koeln.de/

Frommolt P, Thomas RK (2008): Standardized high-throughput evaluation of cell-based compound screens. BMC Bioinformatics, 9(1): 475

Sos ML, Michel K, Zander T, Weiss J, Frommolt P, et al. (2009): Predicting drug susceptibility in non-small cell lung cancers based on genetic lesions. J Clin Invest, 119(6): 1727-40

#Example from a cell line screen (2007). IC50 values are determined for
#the lung cancer cell line HCC2429 and 7 selected compounds.

data(HCC2429_1,HCC2429_2)
write.table(HCC2429_1,file="HCC2429_1.txt",row.names=FALSE,col.names=FALSE,sep="\t")
write.table(HCC2429_2,file="HCC2429_2.txt",row.names=FALSE,col.names=FALSE,sep="\t")

data(mpi384_measure,mpi384_control,mpi384_dilution)
write.table(mpi384_measure,file="mpi384_measure.txt",row.names=FALSE,col.names=FALSE,sep="\t")
write.table(mpi384_control,file="mpi384_control.txt",row.names=FALSE,col.names=FALSE,sep="\t")
write.table(mpi384_dilution,file="mpi384_dilution.txt",row.names=FALSE,col.names=FALSE,sep="\t")

print(ic50.384(files=c("HCC2429_1.txt","HCC2429_2.txt"),
               measure="mpi384_measure.txt",control="mpi384_control.txt",dilution="mpi384_dilution.txt",
               inhib=rep(0.5,7),outdir="./HCC2429_results",normalize="mean"))