PolyFitPlot {EBSeq} | R Documentation

## Fit the mean-var relationship using polynomial regression

### Description

'PolyFitPlot' fits the mean-var relationship using polynomial regression.

### Usage

    PolyFitPlot(X, Y, nterms, xname = "Estimated Mean",
    	yname = "Estimated Var", pdfname = "",
    	xlim =  c(-1,5), ylim = c(-1,7), ChangeXY = F,
    	col = "red")

### Arguments

`X` | The first group of values want to be fitted by the polynomial regression (e.g Mean of the data).
`Y` | The second group of values want to be fitted by the polynomial regression (e.g. variance of the data). The length of Y should be the same as the length of X.
`nterms` | How many polynomial terms want to be used.
`xname` | Name of the x axis.
`yname` | Name of the y axis.
`pdfname` | Name of the plot.
`xlim` | The x limits of the plot.
`ylim` | The y limits of the plot.
`ChangeXY` | If ChangeXY is setted to be TRUE, X will be treated as the dependent variable and Y will be treated as the independent one. Default is FALSE.
`col` | Color of the fitted line.

### Value

The PolyFitPlot function provides a smooth scatter plot of two variables and their best fitting line of polynomial regression.

### Author(s)

Ning Leng

### References

Ning Leng, John A. Dawson, James A. Thomson, Victor Ruotti, Anna I. Rissman, Bart M.G. Smits, Jill D. Haag, Michael N. Gould, Ron M. Stewart, and Christina Kendziorski. EBSeq: An empirical Bayes hierarchical model for inference in RNA-seq experiments. Bioinformatics (2013)

### Examples

    data(IsoList)
    str(IsoList)
    IsoMat = IsoList$IsoMat
    IsoNames = IsoList$IsoNames
    IsosGeneNames = IsoList$IsosGeneNames
    IsoSizes = MedianNorm(IsoMat)
    NgList = GetNg(IsoNames, IsosGeneNames)

    IsoNgTrun = NgList$IsoformNgTrun
    #IsoEBOut = EBTest(Data = IsoMat.small,
    #	NgVector = IsoNgTrun,
    #	Conditions = as.factor(rep(c("C1","C2"), each=5)),
    #	sizeFactors = IsoSizes, maxround = 5)

    #par(mfrow=c(2,2))
    #PolyFitValue = vector("list",3)

    #for(i in 1:3)
    #	PolyFitValue[[i]] = PolyFitPlot(IsoEBOut$C1Mean[[i]],
    #		IsoEBOut$C1EstVar[[i]], 5)

    #PolyAll = PolyFitPlot(unlist(IsoEBOut$C1Mean),
    #	unlist(IsoEBOut$C1EstVar), 5)

    #lines(log10(IsoEBOut$C1Mean[[1]][PolyFitValue[[1]]$sort]),
    #	PolyFitValue[[1]]$fit[PolyFitValue[[1]]$sort],
    #	col="yellow", lwd=2)
    #lines(log10(IsoEBOut$C1Mean[[2]][PolyFitValue[[2]]$sort]),
    #	PolyFitValue[[2]]$fit[PolyFitValue[[2]]$sort],
    #	col="pink", lwd=2)
    #lines(log10(IsoEBOut$C1Mean[[3]][PolyFitValue[[3]]$sort]),
    #	PolyFitValue[[3]]$fit[PolyFitValue[[3]]$sort],
    #	col="green", lwd=2)

    #legend("topleft",c("All Isoforms","Ng = 1","Ng = 2","Ng = 3"),
    #	col = c("red","yellow","pink","green"),
    #	lty=1, lwd=3, box.lwd=2)

[Package EBSeq version 1.26.0 Index]