exon.segment: Binary segmentation of exon data.
In DNAcopy: DNA copy number data analysis

Description Usage Arguments Details Value Author(s) Examples

Compute the binary segmentation statistic, location and approximate p-value.

1	exon.segment(gene, eloc, edat, ngrid=100, tol=1e-6)

`gene`	gene names in the exon data
`eloc`	exon locations within gene
`edat`	exon expressions within gene
`ngrid`	number grid points for the integral
`tol`	tolerance level for calculating nu

The p-values are obtained by applying Siegmund's approximation for the maximal statistic from binary segmenting consecutive segments within a chromosome. These are one-sided test for an increase in expression.

a matrix with three columns. The maximal statistic from binary segmentation, its location and the p-values for each gene.

Venkatraman E. Seshan

# test code on an easy data set
set.seed(25)
gene <- rep(c("A", "B"), c(30,20))
eloc <- c(1:30, 1:20)
edat <- matrix(rnorm(500), 50, 10)
# changes for gene1 in samples 3 & 7
edat[1:30, 3] <- edat[1:30, 3] + rep(0.9*0:1, c(17, 13))
edat[1:30, 7] <- edat[1:30, 7] + rep(1.1*0:1, c(21, 9))
# changes for gene2 in samples 4 & 7
edat[31:50, 4] <- edat[31:50, 4] + rep(1.1*0:1, c(8, 12))
edat[31:50, 7] <- edat[31:50, 7] + rep(1.2*0:1, c(13, 7))
exon.segment(gene, eloc, edat)