monoSmu {lumi} | R Documentation |
Fit the monotonic-constraint spline curve
monoSmu(x, y, newX = NULL, nSupport = min(200, length(x)), nKnots = 6, rotate = FALSE, ifPlot = FALSE, xlab = 'x', ylab = 'y', ...)
x |
a vector represents x values |
y |
a vector represents y values |
newX |
the new values to be transformed. If not provided, "x" will be used. |
nSupport |
downsampled data points |
nKnots |
parameter used by monoSpline |
rotate |
determine whether to rotate the axis with 45 degrees in clockwise, i.e., fit the curve in the MA-plot. |
ifPlot |
determine whether to plot intermediate results |
xlab |
the xlab of the plot |
ylab |
the ylab of the plot |
... |
parameters used by supsmu and plot |
function called by lumiN.rsn. The function first fits a monotonic spline between vector x and y, then transforms the vector newX based on the fitted spline. (After transformation the fitted spline is supposed to be a diagonal line, i.e., x=y)
Return the transformed "newX" based on the smoothed curve
Simon Lin, Pan Du
Lin, S.M., Du, P., Kibbe, W.A., {it Model-based Variance-stabilizing Transformation for Illumina Microarray Data}, submitted
x <- sort(runif(200) * 100) y <- x + rnorm(200) * 10 temp <- monoSmu(x, y, ifPlot=TRUE)