| getPearsonMap {HiTC} | R Documentation |
Generate pearson correlation map, usually used to call chromosomal compartments
getPearsonMap(x, normPerExpected=TRUE, center=TRUE, ...)
x |
object that inherits from class |
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 |
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
## 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"))