The Class SquadSimResServiceImpl contains the information needed to plot the simulation matrix, the prediction map and the correlation circle.
Slots
folder:
Object of class "character", path to the folder to find the SQUAD (1) data.
time:
Object of class "numeric", time point used to get the interpolated activate state value.
ncolor:
Object of class "numeric", number of color code to used in the prediction map. default = 5
legend:
Object of class "vector", contains the name of each node of the model (Must appear in the same order than the simulation).
indexDeno:
Object of class "numeric", the index of the file to used as denominator (the names of each file in the folder should contain an index, i.e 1_xxx.txt), default = 1
method:
Object of class "character", the fitting method to interpolate the curve ("linear" to get a straight line (2) or "lowess" to get a smoothed interpolation (3)).
selectNode:
Object of class "character", contains the name of the node to display.
conditionList:
Object of class "character", list of the perturbation condition names.
Constructor
simResService(folder, time, ncolor, legend, indexDeno, method, selectNode, conditionList): construct a instance of SquadSimResServiceImpl.
Methods
getFittedTable
signature(object = "SquadSimResServiceImpl"): Build and display the table of interpolated/fitted values (see getFittedTable for more details).
plotSimMatrix
signature(object = "SquadSimResServiceImpl"): plot the simulation matrix (see plotSimMatrix for more details).
plotPredMap
signature(object = "SquadSimResServiceImpl"): plot the prediction map (see plotPredMap for more details).
plotCC
signature(object = "SquadSimResServiceImpl"): plot the correlation circle from PCA analyis (see plotCC for more details).
Accessor methods
See examples Section.
Author(s)
Martial Sankar
References
(1) Di Cara A, Garg A, De Micheli G, Xenarios I, Mendoza L (2007) Dynamic simulation of regulatory networks using SQUAD. BMC Bioinformatics 8: 462.
(2) Cleveland, W. S. (1979) Robust locally weighted regression and smoothing scatterplots. J. Amer. Statist. Assoc. 74, 829:836.
(3) Chambers, J. M. (1992) Linear models. Chapter 4 of Statistical Models in S eds J. M. Chambers and T. J. Hastie, Wadsworth And Brooks/Cole.
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> library(SQUADD)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/SQUADD/SquadSimResServiceImpl-class.Rd_%03d_medium.png", width=480, height=480)
> ### Name: SquadSimResServiceImpl-class
> ### Title: Class "SquadSimResServiceImpl"
> ### Aliases: SquadSimResServiceImpl-class SquadSimResServiceImpl
> ### simResService [<-,SquadSimResServiceImpl-method
> ### [,SquadSimResServiceImpl-method
> ### Keywords: classes constructor accessor setter getter
>
> ### ** Examples
>
> fpath <- system.file("extdata", package="SQUADD")
> fileModel <- file.path(fpath,"data_IAA")
> nm <- c("ARF(a)", "ARF(i)", "AR_Genes", "Aux/IAA", "BES1/BZR1", "BIN2", "BR", "BRI1-BAK1","BRR_Genes","BRX","BR_Biosynthesis","BZR1", "DO", "IAA", "IAA_Biosynthesis", "NGA1", "PIN", "SCFTir1","StimAux", "StimBR")
> t <- 50
>
> ## call constructor
> obj <- simResService(folder=fileModel, time=t, ncolor=5,legend=nm, indexDeno=1, method="lowess")
>
> ## Apply method
> tab <- getFittedTable(obj)
> obj["selectNode"] <-c("DO","IAA_Biosynthesis","BR_Biosynthesis", "IAA", "BR")
>
> plotSimMatrix(obj)
/home/ddbj/local/lib64/R/library/SQUADD/extdata/data_IAA/brx_1_normal.txt
/home/ddbj/local/lib64/R/library/SQUADD/extdata/data_IAA/brx_2_brxlof.txt
/home/ddbj/local/lib64/R/library/SQUADD/extdata/data_IAA/brx_3_brrescue.txt
/home/ddbj/local/lib64/R/library/SQUADD/extdata/data_IAA/brx_4_brxarfi.txt
/home/ddbj/local/lib64/R/library/SQUADD/extdata/data_IAA/brx_5_brxarfiRescue.txt
/home/ddbj/local/lib64/R/library/SQUADD/extdata/data_IAA/brx_6_gain.txt
> plotPredMap(obj)
>
> obj["conditionList"] <- c("Normal", "brxlof", "BRrescue","brxarfilof", "brxarfiBRrescue", "brxgof")
> plotCC(obj)
>
> ## getter/setter test
> obj["time"] <- 45
>
>
>
>
>
> dev.off()
null device
1
>