Apply a function on subsets of data frames

This is a parallel version of aggregate.

"bpaggregate"(x, data, FUN, ..., BPREDO=list(), BPPARAM=bpparam())
"bpaggregate"(x, by, FUN, ..., simplify=TRUE, BPREDO=list(), BPPARAM=bpparam())
"bpaggregate"(x, by, FUN, ..., simplify=TRUE, BPREDO=list(), BPPARAM=bpparam())
"bpaggregate"(x, ..., BPREDO=list(), BPPARAM=bpparam())
A data.frame, matrix or a formula.
A list of factors by which x is split; applicable when x is data.frame or matrix.
A data.frame; applicable when x is a formula.
Function to apply.
Additional arguments for FUN.
If set to TRUE, the return values of FUN will be simplified using simplify2array.
An optional BiocParallelParam instance determining the parallel back-end to be used during evaluation.
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.

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.


See aggregate.

  • bpaggregate
  • bpaggregate,formula,BiocParallelParam-method
  • bpaggregate,matrix,BiocParallelParam-method
  • bpaggregate,data.frame,BiocParallelParam-method
  • bpaggregate,ANY,missing-method

if (all(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)

Documentation reproduced from package BiocParallel, version 1.4.0, License: GPL-2 | GPL-3

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