getPearsonMap {HiTC} | R Documentation

## Pearson correlation map

### 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"))

[Package HiTC version 1.26.0 Index]