hts {ic50} | R Documentation |
Simultaneous evaluation of a large number of compound screens on 96- and 384-well plates.
ic50() hts.96(indir=".",plates=2,measure=NULL,control=NULL,dilution=NULL,inhib=NULL, normalize="mean",graphics="mean",outdir="./results") hts.384(indir=".",plates=2,measure=NULL,control=NULL,dilution=NULL,inhib=NULL, normalize="single",graphics="mean",outdir="./results")
indir |
A character specifying the directory which contains the raw data files. |
plates |
Number of plates used for each experiment. |
measure |
Configuration file for the locations of the measurement wells. |
control |
Configuration file for the locations of the control wells. |
dilution |
Configuration for the concentrations in each measurement. |
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. If "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 quantified by the concentration for which a particular fraction (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 hts.96
and hts.384
functions provide a powerful tool
to simultaneously evaluate all data in the specified input directory
indir
. The data files are handled in groups of the size specified
by plates
and the file names should be arranged in a way that
two plates with replicates for the same measurements
are displayed one below the other in a file browser. The data are
expected to be arranged in tab-delimited text files which is the typical
output of appropriate microplate readers. Just as for the
evaluation of a single measurement, the design must be specified by
tab-delimited files for measure
, control
and
dilution
. Details on these are given in the manual of the
default384_measure
and default384_control
files. 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 and each group of data files, a
graphics output is given in the file "dose_response_curves.pdf"
in the
current workspace directory. In addition, the text file
"ic50.txt"
contains a tab-delimted table with the same
evaluation as for the ic50.96
and ic50.384
functions but for all experiments one below the other.
ic50()
starts a GUI-based version of the hts.96
and
hts.384
functions. Preliminary change of the workspace
directory to the folder containing the data will remarkably reduce the
number of mouse clicks.
A data frame with the following columns:
first_file |
Filename of the respective first input file. |
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. |
Peter Frommolt, University of Cologne peter.frommolt@uni-koeln.de
http://www.medizin.uni-koeln.de/kai/imsie/homepages/Peter.Frommolt/
#Example from a non-small cell lung cancer (NSCLC) cell line screen. In #total, 84 samples were screened. The evaluation is exemplarily shown for #the cell lines A549, Calu1, H322 and HCC2429. data(A549_1,A549_2,Calu1_1,Calu1_2,H322_1,H322_2,HCC2429_1,HCC2429_2) dir.create("NSCLC_screen") write.table(A549_1,file="NSCLC_screen/A549_1.txt",row.names=FALSE,col.names=FALSE,sep="\t") write.table(A549_2,file="NSCLC_screen/A549_2.txt",row.names=FALSE,col.names=FALSE,sep="\t") write.table(Calu1_1,file="NSCLC_screen/Calu1_1.txt",row.names=FALSE,col.names=FALSE,sep="\t") write.table(Calu1_2,file="NSCLC_screen/Calu1_2.txt",row.names=FALSE,col.names=FALSE,sep="\t") write.table(H322_1,file="NSCLC_screen/H322_1.txt",row.names=FALSE,col.names=FALSE,sep="\t") write.table(H322_2,file="NSCLC_screen/H322_2.txt",row.names=FALSE,col.names=FALSE,sep="\t") write.table(HCC2429_1,file="NSCLC_screen/HCC2429_1.txt",row.names=FALSE,col.names=FALSE,sep="\t") write.table(HCC2429_2,file="NSCLC_screen/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(hts.384(indir="NSCLC_screen", measure="mpi384_measure.txt",control="mpi384_control.txt",dilution="mpi384_dilution.txt", inhib=rep(0.5,7),outdir="NSCLC_results",normalize="mean"))