| sw.plot(cgh) | R Documentation | 
This function plots the sign-adjusted logratios by their chromosomal location. It can superimpose the location of the highest-scoring island found by the Smith-Waterman algorithm, the results of a robustness analysis, and the expected logratios based on known copy numbers in the test DNA.
  sw.plot(logratio, location = seq(length(logratio)),
    threshold.func = function(x) median(x) + .2 * mad(x),
    sign = -1, highest = TRUE, expected = NULL, rob = NULL, legend = TRUE, 
    xlab = "Chromosomal location", ylab = "Intensity log ratio", ...)
  
| logratio | a vector of logratios, not adjusted for sign or threshold | 
| location | a vector of chromosomal locations corresponding to the log ratios | 
| threshold.func | threshold function: see sw.threshold | 
| sign | sign of logratio adjustment: see sw.threshold | 
| highest | plot location of highest-scoring island if TRUE | 
| expected | a vector of expected copy numbers, or NULL | 
| rob | a vector of robustness scores, or NULL | 
| legend | plot legend if TRUE | 
| xlab | X axis label | 
| ylab | Y axis label | 
| ... | other arguments passed to the 'plot' function | 
T.S.Price
sw
sw.threshold
sw.perm.test
sw.rob
## simluate vector of logratios
set.seed(3)
logratio <- c(rnorm(20) - 1, rnorm(20))
## invert sign of values and subtract threshold to ensure negative mean
x <- sw.threshold(logratio, function(x) median(x) + .2 * mad(x), -1)
## perform permuation test for islands identified
p <- sw.perm.test(x, max.nIslands = NULL, nIter = 1e4)
## calculate robustness scores
r <- sw.rob(x)
## plot results
sw.plot(logratio, seq(length(logratio)),
  function(x) median(x) + .2 * mad(x), sign = -1, rob = r,
  main = paste("Toy dataset, highest-scoring island p =", p[1]))