pca.hic {HiTC} | R Documentation

## Perform Principle Component Analysis on Hi-C contact map

### Description

Perform Principle Component Analysis on Hi-C contact map

### Usage

    pca.hic(x, normPerExpected=TRUE, npc=2, asGRangesList=TRUE,
    gene.gr=NULL, ...)

### Arguments

`x` | object that inherits from class `HTCexp`
`normPerExpected` | normalized by expected interaction using the loess calculation of distance dependency. see normPerExpected
`npc` | numeric; number of first principal component to return
`asGRangesList` | if TRUE a GRangesList object is returned where the scores represent the eigenvector
`gene.gr` | object of class `GenomicRanges` describing the genes position. If used, the A/B compartments classes are defined based on gene density
`...` | additional parameters passed to `normPerExpected` function

### Details

This method was apply by Lieberman-Aiden et al. 2009 to correlate the annotation profiles (genes, ChIP-seq, etc.) with the topological domains observed in Hi-C (see Fig3G of Lieberman-Aiden et al. 2009)

### Value

A list with the eigen vector(s) of the `npc` first principal component(s), and their importance

### 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)

    ## Performed PCA
    pr<-pca.hic(hiC$chr14chr14, npc=1, asGRangesList=TRUE)

[Package HiTC version 1.24.0 Index]