[BioC] logical subscript too long in normalizeRobustSpline

[paul.boutros at utoronto.ca]

Hi again,

Getting this error using robustspline normalization in limma:
Error in normalizeRobustSpline(object$M[, j], object$A[, j], layout, df = df,  : 
        (subscript) logical subscript too long

I'm on:
Win2k SP2
R 2.0
limma 1.8.8

This isn't a general problem with robustspline, as I seem to be able to get it 
to work on other datasets.  Any suggestions on how to debug?

Paul

### CODE ###
targets <- readTargets();
files <- targets[,c("FileNameCy3", "FileNameCy5")];
RG <- read.maimages(files, source="imagene");
RG$genes <- readGAL();
BG <- backgroundCorrect(RG, method="edwards", offset=50);
MA.within <- normalizeWithinArrays(BG, layout, method="robustspline");

### OUTPUT ###
Loading required package: MASS 
Loading required package: splines 
Error in normalizeRobustSpline(object$M[, j], object$A[, j], layout, df = df,  : 
        (subscript) logical subscript too long
> traceback();
3: normalizeRobustSpline(object$M[, j], object$A[, j], layout, df = df, 
       method = robust)
2: switch(method, loess = {
       for (j in 1:narrays) {
           y <- object$M[, j]
           x <- object$A[, j]
           w <- weights[, j]
           object$M[, j] <- loessFit(y, x, w, span = span, iterations = 
iterations)$residuals
       }
   }, printtiploess = {
       if (is.null(layout)) 
           stop("Layout argument not specified")
       ngr <- layout$ngrid.r
       ngc <- layout$ngrid.c
       nspots <- layout$nspot.r * layout$nspot.c
       for (j in 1:narrays) {
           spots <- 1:nspots
           for (gridr in 1:ngr) for (gridc in 1:ngc) {
               y <- object$M[spots, j]
               x <- object$A[spots, j]
               w <- weights[spots, j]
               object$M[spots, j] <- loessFit(y, x, w, span = span, 
                   iterations = iterations)$residuals
               spots <- spots + nspots
           }
       }
   }, composite = {
       if (is.null(layout)) 
           stop("Layout argument not specified")
       if (is.null(controlspots)) 
           stop("controlspots argument not specified")
       ntips <- layout$ngrid.r * layout$ngrid.c
       nspots <- layout$nspot.r * layout$nspot.c
       for (j in 1:narrays) {
           y <- object$M[, j]
           x <- object$A[, j]
           w <- weights[, j]
           f <- is.finite(y) & is.finite(x) & is.finite(w)
           y[!f] <- NA
           fit <- loess(y ~ x, weights = w, span = span, subset = controlspots, 
               na.action = na.exclude, degree = 0, surface = "direct", 
               family = "symmetric", trace.hat = "approximate", 
               iterations = iterations)
           alpha <- global <- y
           global[f] <- predict(fit, newdata = x[f])
           alpha[f] <- (rank(x[f]) - 1)/sum(f)
           spots <- 1:nspots
           for (tip in 1:ntips) {
               y <- object$M[spots, j]
               x <- object$A[spots, j]
               w <- weights[spots, j]
               local <- loessFit(y, x, w, span = span, iterations = iterations)
$fitted
               object$M[spots, j] <- object$M[spots, j] - alpha[spots] * 
                   global[spots] - (1 - alpha[spots]) * local
               spots <- spots + nspots
           }
       }
   }, robustspline = {
       if (is.null(layout)) 
           stop("Layout argument not specified")
       for (j in 1:narrays) object$M[, j] <- normalizeRobustSpline(object$M[, 
           j], object$A[, j], layout, df = df, method = robust)
   })
1: normalizeWithinArrays(BG, layout, method = "robustspline")