segments.p: p-values for the change-points
In DNAcopy: DNA copy number data analysis

Description Usage Arguments Details Value Author(s) Examples

This program computes pseudo p-values and confidence intervals for the change-points found by the circular binary segmentation (CBS) algorithm.

1	segments.p(x, ngrid=100, tol=1e-6, alpha=0.05, search.range=100, nperm=1000)

`x`	an object of class DNAcopy
`ngrid`	number grid points for the integral
`tol`	tolerance level for calculating nu
`alpha`	Confidence level is 1-alpha
`search.range`	statistic is maximized over nu +/- search.range
`nperm`	number of permutations for confidence interval

The p-values are obtained by applying Siegmund's approximation for the maximal statistic from binary segmenting consecutive segments within a chromosome. This p-value is only to give the relative importance of the change-points as the CBS is different from the algorithm used here.

The confidence intervals are obtained by a permutation algorithm. The data are permuted to the left and right of the identified change-point and the location of the maximal binary segmentation statistic computed. The confidence interval is given by the quantiles of the permutation distribution of the locations.

The statistical properties of this confidence interval is unknown. It is used to give an idea of the uncertainity on the location of the change-points as the CBS is different from the algorithm used here.

a data frame with ten columns. The maximal statistic from binary segmentation, the p-values and lower and upper alpha/2 confidence limits (as genomic positions) are added to the six columns from the segment command.

NOTE: THE p VALUES ARE APPROXIMATE TAIL PROBABILITIES. ANY VALUE GREATER THAN 0.1 CAN HAVE LARGE ERROR. p > 1 ARE REPLACED WITH 1.

Venkatraman E. Seshan

# test code on an easy data set
set.seed(25)
genomdat <- rnorm(500, sd=0.1) +
rep(c(-0.2,0.1,1,-0.5,0.2,-0.5,0.1,-0.2),c(137,87,17,49,29,52,87,42))
plot(genomdat)
chrom <- rep(1:2,c(290,210))
maploc <- c(1:290,1:210)
test1 <- segment(CNA(genomdat, chrom, maploc))
segments.p(test1)