createMetageneProfile: Wrapper function to create scaled and non-scaled...

Description Usage Arguments Value Examples

View source: R/GlobalFunctions.R

Description

Metagene plots show the signal enrichment around a region of interest like the TSS or over a predefined set of genes. The tag density of the immunoprecipitation is taken over all RefSeg annotated human genes, averaged and log2 transformed. The same is done for the input. The normalized profile is calculated as the signal enrichment (immunoprecipitation over the input). Two objects are created: a non-scaled profile for the TSS and TES, and a scaled profile for the entire gene, including the gene body. The non-scaled profile is constructed around the TSS/TES, with 2KB up- and downstream regions respectively.

CreateMetageneProfile

Usage

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createMetageneProfile(smoothed.densityChip, smoothed.densityInput,
    tag.shift, annotationID = "hg19", debug = FALSE, mc = 1)

Arguments

smoothed.densityChip

Smoothed tag-density object for ChIP (returned by qualityScores_EM)

smoothed.densityInput

Smoothed tag-density object for Input (returned by qualityScores_EM)

tag.shift

Integer containing the value of the tag shif, calculated by getCrossCorrelationScores()

annotationID

String indicating the genome assembly (Default="hg19")

debug

Boolean, to enter debugging mode. Intermediate files are saved in working directory

mc

Integer, the number of CPUs for parallelization (default=1)

Value

list with 3 objects: scaled profile ("geneBody"), non-scaled profile for TSS (TSS) and TES (TES). Each object is made of a list containing the chip and the input profile

Examples

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## This command is time intensive to run
##
## To run the example code the user must provide two bam files for the ChIP
## and the input and read them with the readBamFile() function. To make it
## easier for the user to run the example code we provide tow bam examples 
## (chip and input) in our ChIC.data package that have already been loaded 
##with the readBamFile() function.

mc=4
finalTagShift=98
## Not run: 

filepath=tempdir()
setwd(filepath)

data("chipSubset", package = "ChIC.data", envir = environment())
chipBam=chipSubset
data("inputSubset", package = "ChIC.data", envir = environment())
inputBam=inputSubset

## calculate binding characteristics 

chip_binding.characteristics<-spp::get.binding.characteristics(
    chipBam, srange=c(0,500), bin=5,accept.all.tags=TRUE)
input_binding.characteristics<-spp::get.binding.characteristics(
    inputBam, srange=c(0,500), bin=5,accept.all.tags=TRUE)

##get chromosome information and order chip and input by it
chrl_final=intersect(names(chipBam$tags),names(inputBam$tags))
chipBam$tags=chipBam$tags[chrl_final]
chipBam$quality=chipBam$quality[chrl_final]
inputBam$tags=inputBam$tags[chrl_final]
inputBam$quality=inputBam$quality[chrl_final]

##remove sigular positions with extremely high read counts with 
##respect to the neighbourhood
selectedTags=removeLocalTagAnomalies(chipBam, inputBam, 
chip_binding.characteristics, input_binding.characteristics)

inputBamSelected=selectedTags$input.dataSelected
chipBamSelected=selectedTags$chip.dataSelected

##smooth input and chip tags
smoothedChip <- tagDensity(chipBamSelected, 
    tag.shift = finalTagShift, mc = mc)
smoothedInput <- tagDensity(inputBamSelected, 
    tag.shift = finalTagShift, mc = mc)

##calculate metagene profiles
Meta_Result <- createMetageneProfile(
    smoothed.densityChip = smoothedChip, 
    smoothed.densityInput = smoothedInput, 
    tag.shift = finalTagShift, mc = mc)

## End(Not run)

ChIC documentation built on Nov. 1, 2018, 2:25 a.m.