| sw(cgh) | R Documentation | 
Perform the Smith-Waterman algorithm on a vector of real values.
sw(x, max.nIslands = NULL, trace = FALSE)
| x | a vector of real values | 
| max.nIslands | the number of iterations of the algorithm performed. Each iteration finds the next highest-scoring 'island' of positive values. Set to NULL to find all islands | 
| trace | print verbose output if TRUE | 
The Smith-Waterman algorithm detects 'islands' of positive scores in a vector of
real values. The input values should have a negative mean. The algorithm can be
used to identify regions of copy number change in microarray fluorescence
logratios, once the logratios have been adjusted for sign and a suitable
threshold value subtracted to ensure a negative mean: see sw.threshold
| x | the input vector | 
| s | a numeric vector containing the partial sums after one iteration of the Smith-Waterman algorithm | 
| score | a numeric vector of island scores | 
| start | a numeric vector of indices identifying the start of each island | 
| length | a numeric vector of island lengths | 
T.S.Price
Smith TF, Waterman MS. Identification of common molecular subsequences. J Mol Biol. 1981;147(1):195-7.
sw.threshold
sw.perm.test
sw.rob
sw.plot
## 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), sign = -1) ## perform Smith-Waterman algorithm sw(x, trace = TRUE)