normLGF: Local Genomic Feature (LGF) normalization

In bioinfo-pf-curie/HiTC: High Throughput Chromosome Conformation Capture analysis

Description

Parametric model to remove systematic biases in the raw contact maps

Usage

normLGF(x, family=c("poisson", "nb"))

Arguments

x	object that inherits from class HTCexp
family	parametric model to fit (poisson or nb)

Details

This function implements the HiCNorm method proposed by Hu et al. Briefly, the method uses a generalized linear model to correct the systematic biases (effective fragment length, GC content, mappability) in a Hi-C contact map.

Value

Returns a HTCexp object with a normalized contact map.

Author(s)

N. Servant, M. Hu, S. Selvaraj

References

Hu M, Deng K, Selvaraj S, Qin Z, Ren B, Liu JS. HiCNorm: removing biases in Hi-C data via Poisson regression. Bioinformatics. 2012;28(23):3131-3.

See Also

getAnnotatedRestrictionSites, setGenomicFeatures

Examples

## Not run: 
require(HiTC)
require(BSgenome.Hsapiens.UCSC.hg18)

##Lieberman data
exDir <- system.file("extdata", package="HiTC")
l <- sapply(list.files(exDir, pattern=paste("HIC_gm06690_"), full.names=TRUE),
            import.my5C)
hiC <- HTClist(l)
hiC <- hiC[isIntraChrom(hiC)]
names(hiC)

## Mappability data From http://hgdownload.cse.ucsc.edu/goldenPath/hg18/encodeDCC/wgEncodeMapability/
map_hg18<- import("wgEncodeCrgMapabilityAlign100mer.bw", format="BigWig")

## Get the genomic feature of the chromosome 12
hiC_annot <- HTClist(lapply(hiC, setGenomicFeatures, resSite="AAGCTT", overhangs5=1, genomePack="BSgenome.Hsapiens.UCSC.hg18", wingc=200, mappability=map_hg18, winmap=500))
hiC_annot$chr12chr12

## Normalize the data
hiCnorm <- HTClist(lapply(hiC_annot, normLGF))


## End(Not run)

bioinfo-pf-curie/HiTC documentation built on May 17, 2019, 6:39 p.m.