rpMatrix {recoup} | R Documentation

## Reads per million profile matrices for plotting

### Description

This function fills the `profile` field in the main `input` argument in `recoup` function by calculating profile matrices using reads per million (rpm) or reads per kb per million reads (rpkm) over binned genomic areas of interest, instead of genomic coverage signals. The profile matrices are used for later plotting.

### Usage

        rpMatrix(input, mainRanges, flank, binParams,
            strandedParams = list(strand = NULL, ignoreStrand = TRUE),
            rc = NULL)

### Arguments

`input` | an input list as in `recoup` but with the `ranges` field of each member filled (e.g. after using `preprocessRanges`.
`mainRanges` | the `genome` from `recoup` as a `GRanges` object (e.g. the output from `makeGRangesFromDataFrame`).
`flank` | see the `flank` argument in the main `recoup` function.
`binParams` | see the `binParams` argument in the main `recoup` function.
`strandedParams` | see the `strandedParams` argument in the main `recoup` function.
`rc` | fraction (0-1) of cores to use in a multicore system. It defaults to `NULL` (no parallelization).

### Details

Regarding the calculation of `rpm` and `rpkm` values, the calculations slightly differ from the default defintions of these measurements in the sense that they are also corrected for the bin lengths so as to acquire human-friendly values for plotting.

Note that the genomic ranges (BAM/BED files) must be imported before using this function (as per the default `recoup` pipeline). We plan to support streaming directly from BAM files in the future.

### Value

Same as input with the `profile` fields filled.

### Author(s)

Panagiotis Moulos

### Examples

    # Load some data
    data("recoup_test_data",package="recoup")
    # Do some work
    testGenomeRanges <- makeGRangesFromDataFrame(df=test.genome,
        keep.extra.columns=TRUE)
    w <- width(testGenomeRanges)
    testGenomeRanges <- promoters(testGenomeRanges,upstream=2000,downstream=0)
    testGenomeRanges <- resize(testGenomeRanges,width=w+4000)
    test.input <- rpMatrix(
        test.input,
        mainRanges=testGenomeRanges,
        flank=c(2000,2000),
        binParams=list(flankBinSize=50,regionBinSize=150,binType="fixed",
            sumStat="mean",interpolation="spline"),
        rc=0.1
    )

[Package recoup version 1.18.0 Index]