getPearsonMap: Pearson correlation map
In HiTC: High Throughput Chromosome Conformation Capture analysis

Description Usage Arguments Details Value Author(s) See Also Examples

Generate pearson correlation map, usually used to call chromosomal compartments

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

`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`

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

A HTCexp object

N. Servant, B. Lajoie, R. McCord

normPerExpected

## 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"))