getPearsonMap: Pearson correlation map

In bioinfo-pf-curie/HiTC: High Throughput Chromosome Conformation Capture analysis

Description

Generate pearson correlation map, usually used to call chromosomal compartments

Usage

getPearsonMap(x, normPerExpected=TRUE, center=TRUE, ...)

Arguments

x	object that inherits from class HTCexp
normPerExpected	normalized by expected interaction using the loess calculation of distance dependency. see normPerExpected
center	default=true. center the observed/expected map before calculating the Pearson correlation
...	additional parameters passed to normPerExpected

Details

The function returns an HTCexp object with Pearson correlation map. This is usually the first step of the Principal Component Analysis (see pca.hic). Centering the rows of the observed/expected matrix allows to avoid bias to due to ranges of interaction counts. If true, the correlation of small values should be as valuable as correlation of large values

Value

A HTCexp object

Author(s)

N. Servant, B. Lajoie, R. McCord

See Also

normPerExpected

Examples

## Get Lieberman-Aiden Hi-C data
exDir <- system.file("extdata", package="HiTC")
l <- sapply(list.files(exDir, pattern=paste("HIC_gm06690_"), full.names=TRUE),
import.my5C)
hiC <- HTClist(l)

## get Pearson correlation map
pm <- getPearsonMap(hiC$chr14chr14)
mapC(HTClist(pm), maxrange=1, col.pos=c("black","red"), col.neg=c("black","blue"))

bioinfo-pf-curie/HiTC documentation built on May 17, 2019, 6:39 p.m.