bpaggregate {BiocParallel} | R Documentation

## Apply a function on subsets of data frames

### Description

This is a parallel version of `aggregate`.

### Usage

    ## S4 method for signature 'formula,BiocParallelParam'
    bpaggregate(x, data, FUN, ...,
        BPREDO=list(), BPPARAM=bpparam())

    ## S4 method for signature 'data.frame,BiocParallelParam'
    bpaggregate(x, by, FUN, ...,
        simplify=TRUE, BPREDO=list(), BPPARAM=bpparam())

    ## S4 method for signature 'matrix,BiocParallelParam'
    bpaggregate(x, by, FUN, ...,
        simplify=TRUE, BPREDO=list(), BPPARAM=bpparam())

    ## S4 method for signature 'ANY,missing'
    bpaggregate(x, ..., BPREDO=list(), BPPARAM=bpparam())

### Arguments

`x` | A `data.frame`, `matrix` or a formula.
`by` | A list of factors by which `x` is split; applicable when `x` is `data.frame` or `matrix`.
`data` | A `data.frame`; applicable when `x` is a `formula`.
`FUN` | Function to apply.
`...` | Additional arguments for `FUN`.
`simplify` | If set to `TRUE`, the return values of `FUN` will be simplified using `simplify2array`.
`BPPARAM` | An optional `BiocParallelParam` instance determining the parallel back-end to be used during evaluation.
`BPREDO` | A `list` of output from `bpaggregate` with one or more failed elements. When a list is given in `BPREDO`, `bpok` is used to identify errors, tasks are rerun and inserted into the original results.

### Details

`bpaggregate` is a generic with methods for `data.frame` `matrix` and `formula` objects. `x` is divided into subsets according to factors in `by`. Data chunks are sent to the workers, `FUN` is applied and results are returned as a `data.frame`.

The function is similar in spirit to `aggregate` from the stats package but `aggregate` is not explicitly called. The `bpaggregate` `formula` method reformulates the call and dispatches to the `data.frame` method which in turn distributes data chunks to workers with `bplapply`.

### Value

See `aggregate`.

### Author(s)

Martin Morgan mailto:mtmorgan@fhcrc.org.

### Examples

    if (require(Rsamtools) && require(GenomicAlignments)) {

      fl <- system.file("extdata", "ex1.bam", package="Rsamtools")
      param <- ScanBamParam(what = c("flag", "mapq"))
      gal <- readGAlignments(fl, param=param)

      ## Report the mean map quality by range cutoff:
      cutoff <- rep(0, length(gal))
      cutoff[start(gal) > 1000 & start(gal) < 1500] <- 1
      cutoff[start(gal) > 1500] <- 2
      bpaggregate(as.data.frame(mcols(gal)$mapq), list(cutoff = cutoff), mean)

    }

[Package BiocParallel version 1.14.2 Index]