scoreMergedBins {RIPSeeker} | R Documentation

## Average log odd scores over bins being merged into a single region

### Description

Sum, normalize the read counts, and average the logOdd score over the bins being merged into a single enriced region.

### Usage

    scoreMergedBins(findOverlapsHits, unmergedGRAll, mergedGRAll)

### Arguments

`findOverlapsHits` | Output from `findOverlaps` as two columns indices with the first column containing the indices for unmerged GRanges and the second column the indices of the matched merged GRanges.
`unmergedGRAll` | GRanges before merging.
`mergedGRAll` | GRanges after merging.

### Details

The consecutive RIP-bins predicted by the Viterbi function (See `nbh_vit`) are merged into a single RIP region. An aggregate RIPScore as the averaged RIPScores over the associated merged bins is assigned to each merged RIP region. In the RIPSeeker workflow, the averaged RIPScore then becomes the representative score for the region and subject to significance test carried out in `seekRIP`.

### Value

A merged GRanges each with scores including summed read count, averaged log odd scores, and FPK (fragment per kilobase of region length). The latter score represent a normalized read count.

### Note

This function is expected to be called only from `logScoreWithoutControl` and `logScoreWithControl`.

### Author(s)

Yue Li

### See Also

`seekRIP, computeLogOdd logScoreWithControl, logScoreWithoutControl`

### Examples

    if(interactive()) { # see example in seekRIP
    # Retrieve system files
    extdata.dir <- system.file("extdata", package="RIPSeeker")

    bamFiles <- list.files(extdata.dir, ".bam$", recursive=TRUE, full.names=TRUE)

    bamFiles <- grep("PRC2", bamFiles, value=TRUE)

    # Parameters setting
    binSize <- 1e5					# use a large fixed bin size for demo only
    multicore <- FALSE			# use multicore
    strandType <- "-"				# set strand type to minus strand

    ################ run main function for HMM inference on all chromosomes ################
    mainSeekOutputRIP <- mainSeek(bamFiles=
        grep(pattern="SRR039214", bamFiles, value=TRUE, invert=TRUE),
    		binSize=binSize, strandType=strandType,
    		reverseComplement=TRUE, genomeBuild="mm9",
    		uniqueHit = TRUE, assignMultihits = TRUE,
    		rerunWithDisambiguatedMultihits = TRUE,
    		multicore=multicore, silentMain=FALSE, verbose=TRUE)

    nbhGRRIP <- mainSeekOutputRIP$nbhGRList$chrX

    logOddScore <- computeLogOdd(nbhGRRIP)

    values(nbhGRRIP) <- cbind(as.data.frame(values(nbhGRRIP)), logOddScore)

    enrichIdx <- which(values(nbhGRRIP)$viterbi_state == 2)

    unmergedRIP <- nbhGRRIP[enrichIdx]

    mergedRIP <- reduce(unmergedRIP, min.gapwidth = median(width(unmergedRIP) ))

    overlapIdx <- findOverlaps(mergedRIP, unmergedRIP)

    # a list with query hits as names and subject hits as items
    findOverlapsHits <- split(overlapIdx, queryHits(overlapIdx))

    # get the score for the first merged region
    x <- scoreMergedBins(findOverlapsHits[[1]], unmergedRIP, mergedRIP)

    # get scores for all of the merged regions
    mergedRIPList <- lapply(split(overlapIdx, queryHits(overlapIdx)),

    			scoreMergedBins, unmergedRIP, mergedRIP)

    names(mergedRIPList) <- NULL

    mergedRIP <- do.call(c, mergedRIPList)

    # logOddScore is the averaged logOddScore across merged bins
    mergedRIP
    }

[Package RIPSeeker version 1.24.0 Index]