makeCNOlist: Make a CNOlist structure
In CellNOptR: Training of boolean logic models of signalling networks using prior knowledge networks and perturbation data

Description Usage Arguments Details Value Author(s) References See Also Examples

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.

1	makeCNOlist(dataset, subfield, verbose=TRUE)

`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.

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.

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.

C. Terfve, T. Cokelaer

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.

readMIDAS, CNOlist-class

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)

Loading required package: RBGL
Loading required package: graph
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: ‘BiocGenerics’

The following objects are masked from ‘package:parallel’:

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from ‘package:stats’:

    IQR, mad, sd, var, xtabs

The following objects are masked from ‘package:base’:

    anyDuplicated, append, as.data.frame, basename, cbind, colnames,
    dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
    grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
    rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which.max, which.min

Loading required package: hash
hash-2.2.6.1 provided by Decision Patterns

Loading required package: RCurl
Loading required package: Rgraphviz
Loading required package: grid
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Attaching package: ‘XML’

The following object is masked from ‘package:graph’:

    addNode

Loading required package: ggplot2
[1] TRUE TRUE TRUE
[1] "Your data set comprises  18 conditions (i.e. combinations of time point and treatment)"
[1] "Your data set comprises measurements on  7  different species"
[1] "Your data set comprises  4 stimuli/inhibitors and 1 cell line(s) ( mock )"
[1] "Please be aware that CNO only handles measurements on one cell line at this time."
[1] "Your data file contained 'NaN'. We have assumed that these were missing values and replaced them by NAs."
[1] "Please be aware that if you only have some conditions at time zero (e.g.only inhibitor/no inhibitor), the measurements for these conditions will be copied across matching conditions at t=0"