getCounts {segmentSeq} | R Documentation

## Gets counts from alignment data from a set of genome segments.

### Description

A function for extracting count data from an `alignmentData` object given a set of segments defined on the genome.

### Usage

    getCounts(segments, aD, preFiltered = FALSE, adjustMultireads = TRUE,
      useChunk = FALSE, cl)

### Arguments

`segments` | A `GRanges` object which defines a set of segments for which counts are required.
`aD` | An `alignmentData` object.
`preFiltered` | The function internally cleans the data; however, this may not be needed and omitting these steps may save computational time. See Details.
`adjustMultireads` | If working with methylation data, this option toggles an adjustment for reads that align to multiple locations on the genome. Defaults to TRUE.
`useChunk` | If all segments are within defined ‘chunks’ of the alignmentData object, speed increases if this is set to TRUE. Otherwise, counts may be inaccurate. Defaults to FALSE.
`cl` | A SNOW cluster object, or NULL. See Details.

### Details

The function extracts count data from `alignmentData` object 'aD' given a set of segments. The non-trivial aspect of this function is that at a segment which contains a tag that matches to multiple places in that segment (and thus appears multiple times in the `alignmentData` object) should count it only once.

If `preFiltered = FALSE` then the function allows for missing (NA) data in the segments, unordered segments and duplicated segments. If the segment list has no missing data, is already ordered, and contains no duplications, then computational time can be saved by setting `preFiltered = TRUE`.

A `cluster` object (package: snow) is recommended for parallelisation of this function when using large data sets. Passing NULL to this variable will cause the function to run in non-parallel mode.

In general, this function will probably not be accessed by the user as the `processAD` function includes a call to `getCounts` as part of the standard processing of an `alignmentData` object into a `segData` object.

### Value

If ‘as.matrix’, a matrix, each column of which corresponds to a library in the `alignmentData` object ‘aD’ and each row to the segment defined by the corresponding row in ‘segments’. Otherwise an equivalent `DataFrame` object.

### Author(s)

Thomas J. Hardcastle

### See Also

`processAD`

### Examples

    # Define the files containing sample information.

    datadir <- system.file("extdata", package = "segmentSeq")
    libfiles <- c("SL9.txt", "SL10.txt", "SL26.txt", "SL32.txt")

    # Establish the library names and replicate structure.

    libnames <- c("SL9", "SL10", "SL26", "SL32")
    replicates <- c(1,1,2,2)

    # Process the files to produce an 'alignmentData' object.

    alignData <- readGeneric(file = libfiles, dir = datadir, replicates =
    replicates, libnames = libnames, gap = 100)

    # Get count data for three arbitrarily chosen segments on chromosome 1.

    getCounts(segments = GRanges(seqnames = c(">Chr1"),
              IRanges(start = c(1,100,2000), end = c(40,3000,5000))),
              aD = alignData, cl = NULL)

[Package segmentSeq version 2.18.0 Index]