region.position: Identify Enriched Regions

In tileHMM: Hidden Markov Models for ChIP-on-Chip Analysis

Description

After calling individual probes enriched or non-enriched this function can be used to combine probes into enriched regions.

Usage

region.position(probe.calls, region = TRUE)

Arguments

probe.calls	A vector of probe calls.
region	Probe call that should be combined into regions.

Value

A matrix with two rows and as many columns as there are enriched regions. The first row gives the index of the first probe of each region the second row the index of the last probe inside each region.

Author(s)

Peter Humburg

Examples

## create two state HMM with t distributions
state.names <- c("one","two")
transition <- c(0.1, 0.02)
location <- c(1, 2)
scale <- c(1, 1)
df <- c(4, 6)
model <- getHMM(list(a=transition, mu=location, sigma=scale, nu=df), 
    state.names)

## obtain observation sequence from model
obs <- sampleSeq(model, 100)

## compute most likely state sequence for obs
vit.res <- viterbi(model, obs)

## find regions attributed to state "one"
reg.pos <- region.position(vit.res$stateSeq, region="one")

tileHMM documentation built on May 30, 2017, 3:41 a.m.