Make a CNOlist structure

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Description

This function takes as input the output of readMIDAS and extracts the elements that are needed in a CNO project. Instead, please use the CNOlist class to read a MIDAS file that will be converted to a CNOlist.

Usage

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makeCNOlist(dataset, subfield, verbose=TRUE)

Arguments

dataset

output of readMIDAS

subfield

TRUE or FALSE, specifies if the column headers contain subfields or not i.e. if I should look for TR:sthg:sthg or just TR:sthg.

verbose

logical (default to TRUE) print information on the screen.

Details

Be aware that most of the functions in this package, including this one, expect the data to contain measurements at time 0, but these should all be equal to zero according to the normalisation procedure that should be used. Therefore, if you have one time point, the files valueSignals contains two matrices, one for t0 and one for t1.

If there are replicate rows in the MIDAS file (i.e., identical cues and identical time), this function averages the values of the measurements for these replicates.

Columns with the following tags are ignored: NOINHIB, NO-INHIB, NO-LIG, NOCYTO.

Value

a CNOlist with fields

namesCues

a vector of names of cues

namesStimuli

a vector of names of stimuli

namesInhibitors

a vector of names of inhibitors

namesSignals

a vector of names of signals

timeSignals

a vector of times

valueCues

a matrix of dimensions nConditions x nCues, with 0 or 1 if the cue is present or absent in the particular condition

valueInhibitors

a matrix of dimensions nConditions x nInhibitors, with 0 or 1 if the inhibitor is present or absent in the particular condition

valueStimuli

of dimensions nConditions x nStimuli, with 0 or 1 if the stimuli is present or absent in the particular condition

valueSignals

a list of the same length as timeSignals, each element containing a matrix of dimensions nConditions x nsignals, with the measurements.

valueVariances

a list of the same length as timeSignals, each element containing a matrix of dimensions nConditions x nsignals, with the standard deviation of the replicates.

Author(s)

C. Terfve, T. Cokelaer

References

J. Saez-Rodriguez, L. G. Alexopoulos, J. Epperlein, R. Samaga, D. A. Lauffenburger, S. Klamt and P. K. Sorger. Discrete logic modeling as a means to link protein signaling networks with functional analysis of mammalian signal transduction, Molecular Systems Biology, 5:331, 2009.

See Also

readMIDAS, CNOlist-class

Examples

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tmpdir<-tempdir()
setwd(tmpdir)
cpfile<-dir(system.file("ToyModel",package="CellNOptR"),full=TRUE)
file.copy(from=cpfile,to=getwd(),overwrite=TRUE)
dataToy<-readMIDAS(MIDASfile='ToyDataMMB.csv')
CNOlistToy<-makeCNOlist(dataset=dataToy,subfield=FALSE)

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