R: Compute and plot distribution of average coverage or relative...

getMetaCoverage {wavClusteR}

R Documentation

Compute and plot distribution of average coverage or relative log-odds as metagene profile using identified clusters

Description

Transcriptome-wide identified clusters are used to generate a metagene profile by binning gene bodies. Within each bin, the distribution of the average cluster coverage or of the relative log-odds is computed.

Usage

getMetaCoverage(clusters, txDB = NULL, upstream = 1e3, downstream =
1e3, nBins = 40, nBinsUD = 10, minLength = 1, genome = 'hg19', tablename =
'ensGene', odds = FALSE, plot = TRUE, verbose = TRUE, ...)

Arguments

`clusters`	GRanges object containing individual clusters as identified by the getClusters function
`txDB`	TranscriptDb object obtained through a call to the `makeTxDbFromUCSC` function in the `GenomicFeatures` package. Default is NULL, namely the object will be fetched internally
`upstream`	An integer corresponding to the number of bases to be considered upstream the gene. Default is 1000
`downstream`	An integer corresponding to the number of bases to be considered downstream the gene. Default is 1000
`nBins`	An integer corresponding to the number of bins to be used to partition the genes. Default is 40
`nBinsUD`	An integer corresponding to the number of bins to be used to partion upstream and downstream regions. Defauls is 10, i.e. the bin size is 100 bases for the default extension
`minLength`	An integer indicating the the minimum required length of a gene in order for it to be considered. Default is 1, i.e. all genes are considered
`genome`	A character specifying the genome abbreviation used by UCSC. Available abbreviations are returned by a call to `ucscGenomes()[ , "db"]`. Default is "hg19" (human genome)
`tablename`	A character specifying the name of the UCSC table containing the transcript annotations to retrieve. Available table names are returned by a call to `supportedUCSCtables()`. Default is "ensGene", namely ensembl gene annotations
`odds`	Logical, if TRUE relative log-odds distributions are shown instead of mean coverage
`plot`	Logical, if TRUE a dotchart with cluster annotations is produced
`verbose`	Logical, if TRUE processing steps are printed
`...`	Additional parameters to be passed to the `plot` function

Value

Called for its effects.

Author(s)

Federico Comoglio

References

Comoglio F*, Sievers C* and Paro R, wavClusteR: an R package for PAR-CLIP data analysis, submitted

Examples


require(BSgenome.Hsapiens.UCSC.hg19)

data( model, package = "wavClusteR" ) 

filename <- system.file( "extdata", "example.bam", package = "wavClusteR" )
example <- readSortedBam( filename = filename )
countTable <- getAllSub( example, minCov = 10, cores = 1 )
highConfSub <- getHighConfSub( countTable, supportStart = 0.2, supportEnd = 0.7, substitution = "TC" )
coverage <- coverage( example )
clusters <- getClusters( highConfSub = highConfSub, 
                         coverage = coverage, 
                         sortedBam = example, 
	                 method = 'mrn', 
	                 cores = 1, 
	                 threshold = 2 ) 

fclusters <- filterClusters( clusters = clusters, 
		             highConfSub = highConfSub, 
        		     coverage = coverage,
			     model = model, 
			     genome = Hsapiens, 
		             refBase = 'T', 
		             minWidth = 12 )
## Not run: getMetaCoverage( clusters = fclusters, odds = FALSE )

[Package wavClusteR version 2.22.0 Index]