pca.hic: Perform Principle Component Analysis on Hi-C contact map

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

View source: R/pca.R

Description

Perform Principle Component Analysis on Hi-C contact map

Usage

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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

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## 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)

HiTC documentation built on Nov. 8, 2020, 8:27 p.m.