aroma.cn (version 0.7.3)

findAtomicAberrations.CopyNumberRegions: Finds all possible atomic regions

Description

Finds all possible atomic regions of a certain length.

Usage

## S3 method for class 'CopyNumberRegions':
findAtomicAberrations(cnr, data, H=1, alpha=0.02, ..., verbose=FALSE)

Arguments

cnr

The segments defining the partitioning of the data.

data

The data used to test for equality.

H

A positive integer specifying how many segments each atomic abberation should contain.

alpha

A double in [0,1] specifying the significance level for testing the null-hypothesis that the flanking segments are equal.

...

Not used.

verbose

See Verbose.

Value

• Returns a data.frame with K rows, where K >= 0 is the number of atomic aberrations found.

Details

An aberration of length H is defined as any H consecutive segments. Each aberrations has two flanking segments on each side. Regardless of the content of the aberration, it is possible to test the null-hypothesis that the two flanking segments are equal or not. The two flanking regions are said to be equal, if the null-hypothesis of being equal is not rejected. If the two flanking regions are called equal, then the contained abberation (of length H) is called atomic, otherwise not. For consistency one may also define atomic aberrations of length H=0. Consider that an imaginary aberration of zero length splits a single segment into to flanking segments. Then by construction those two segments are equal. The case where H=0 is still not implemented.

See Also

...

Examples

# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Local functions
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
xAxisBar <- function(x0, x1=NULL, y=par("usr")[3], lwd=4, col=par("col"), length=0.04, xpd=FALSE, ...) {
  if (is.null(x1)) {
    x1 <- x0[2];
    x0 <- x0[1];
  }
  arrows(x0=x0, x1=x1, y0=y, code=3, angle=90, length=length, lwd=lwd, col=col, xpd=xpd, lend=2, ...);
} # xAxisBar()


verbose <- Arguments$getVerbose(-8, timestamp=TRUE);

# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Simulating copy-number data
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Build up CN profile generation by generation
pT <- cnr(1,2000, 2) +
     cnr(1000,1500) +
     cnr(1000,1250) +
     cnr(1650,1800) +
     cnr(200,300) - cnr(650,800);
print(pT);

# Simulate data from the track
cn <- simulateRawCopyNumbers(pT, n=2000, sd=1/2);
print(cn);


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Find atomic aberrations
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
subplots(4, ncol=1);
par(mar=c(2,4,1,1)+0.1);

# Plot observed and true signals
plot(cn, col="#aaaaaa", ylim=c(0,5));
drawLevels(pT, col="white", lwd=4, lty=1);
drawLevels(pT, col="black", lwd=3, lty=6);
stext(side=3, pos=1, line=-1, ""H=0"", cex=1.5);

for (H in 1:3) {
  plot(cn, col="#aaaaaa", ylim=c(0,5));
  drawLevels(pT, col="white", lwd=4, lty=1);
  drawLevels(pT, col="black", lwd=3, lty=6);
  col <- H+1;
  stext(side=3, pos=1, line=-1, sprintf("H=%d", H), cex=1.5, col=col);
  par <- par("usr");
  y0 <- par("usr")[3];
  y1 <- par("usr")[4];
  dy <- 0.05*(y1-y0);
 
  fit <- findAtomicAberrations(cnr=pT, data=cn, H=H, verbose=verbose);
  df <- fit$res;
 
  for (kk in seq(length=nrow(df))) {
    dfKK <- df[kk,];
    segments <- as.integer(dfKK[,c("firstRegion", "lastRegion")]);
    segments <- segments[1]:segments[2];
    xRange <- as.double(dfKK[,c("start", "stop")]);
    cnrKK <- subset(pT, subset=segments);
    drawLevels(cnrKK, col=col, lwd=3);
    x <- xRange/1e6;
    y <- y0 + 0.2*dy;
    xAxisBar(x0=x[1], x1=x[2], y=y, col=col);
    box();
  }
} # for (H ...)