Last data update: 2014.03.03

R: Calculates the sequence pattern densities at genome wide...
MEDIPS.couplingVectorR Documentation

Calculates the sequence pattern densities at genome wide windows.

Description

The function calculates the local densities of a defined sequence pattern (e.g. CpGs) and returns a COUPLING SET object which is necessary for normalizing MeDIP data.

Usage

MEDIPS.couplingVector(pattern="CG", refObj=NULL)

Arguments

pattern

defines the sequence pattern, e.g. CG for CpGs.

refObj

a MEDIPS Set or MEDIPS ROI Set that serves as reference for the genome and window parameters.

Value

A COUPLING SET object.

Author(s)

Lukas Chavez

Examples


library("MEDIPSData")
library("BSgenome.Hsapiens.UCSC.hg19")

data(hESCs_MeDIP)
CS = MEDIPS.couplingVector(pattern="CG", refObj=hESCs_MeDIP)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(MEDIPS)
Loading required package: BSgenome
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: GenomicRanges
Loading required package: Biostrings
Loading required package: XVector
Loading required package: rtracklayer
Loading required package: Rsamtools
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/MEDIPS/MEDIPS.couplingVector.Rd_%03d_medium.png", width=480, height=480)
> ### Name: MEDIPS.couplingVector
> ### Title: Calculates the sequence pattern densities at genome wide
> ###   windows.
> ### Aliases: MEDIPS.couplingVector
> 
> ### ** Examples
> 
> 
> library("MEDIPSData")
> library("BSgenome.Hsapiens.UCSC.hg19")
> 
> data(hESCs_MeDIP)
> CS = MEDIPS.couplingVector(pattern="CG", refObj=hESCs_MeDIP)
Get genomic sequence pattern positions...
Searching in chr22 ...[ 578097 ] found.
Number of identified  CG  pattern:  578097 
Calculating genomic coordinates...
Creating Granges object for genome wide windows...
Counting the number of CG's in each window...
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>