MAPlot2 {aCGH.Spline} | R Documentation |
Produce a MA-plot showing points fitted and point interpolated.
MAPlot2(x, raw, ntyp="percentile", p=0.68, fact=4.5, segN=FALSE, sn=0.75, pch=46, Fitcol="green", Intcol="red", ylim=c(-5,5), xlim=c(0,20), xlab="log2(mean(cy5, cy3))", ylab="log2(cy5/cy3)", main="MA-plot")
x |
- the ".temp" formatted data structure after normalisation. |
raw |
- the".temp" formatted data structure before normalisation. |
ntyp |
- the type of noise calculation to use, c("percentile", "derivative", "combined"), defaults to "percentile". |
p |
- numeric value between 0 and 1, the quantile to use. |
fact |
- numeric value, the factor by which the noise estimation will be rised. |
segN |
- use segmentation prior to noise estimation TRUE or FALSE (see segN). |
sn |
- the segmentation threshold. |
pch |
- the point character to use defaults to 46. |
Fitcol |
- the point color to use for the points used during spline fitting, defaults to "green". |
Intcol |
- the point color to use for the points excluded from spline fitting, defaults to "red". |
xlim |
- the x-axis limits defaults to c(0,20). |
ylim |
- the y-axis limits defaults to c(-5,5). |
xlab |
- the label for the x-axis. |
ylab |
- the label for the y-axis. |
main |
- the main title for the plot. |
MAplot showing relative number of points considered to be outside the normal distribution.
Points outside the interpolation threshold are not used during the spline fitting. We believe that these points are highly unrealiable for assessing the dye bias.
Tomas William Fitzgerald
# Create some noisy data with a bias v = seq(1,100000,0.5) d = sin(2*pi/500 * v) nd = d + rnorm(length(d),0,100) + 1000 dd = sin(2*pi/1000 * v) ndd = dd + rnorm(length(dd),0,120) + 1000 ## Create ".temp" data stucture mat = matrix(ncol=8,nrow=length(dd)) mat[,1] = log2(nd/ndd) mat[,2] = nd mat[,3] = ndd mat[,4] = 0 mat[,5] = 0 mat[,6] = 0 mat[,7] = 0 mat[,8] = 0 # Add a few outliers mat[100:150,1] = mat[100:150,1] * 1.5 mat[100:150,2] = mat[100:150,2] / 1.5 # Run Jspline and plot aa = Jspline(mat) MAPlot2(aa, mat, ylim=c(-1.5,1.5),xlim=c(9.4,10.4))