An Introduction to the bigmemoryExtras Package

BiocStyle::markdown()

Introduction

This package defines a "BigMatrix" ReferenceClass which adds safety and convenience features to the filebacked.big.matrix class from the bigmemory package. BigMatrix protects against segfaults by monitoring and gracefully restoring the connection to on-disk data. We provide utilities for using BigMatrix-derived classes as assayData matrices within the Biobase package's eSet family of classes. BigMatrix provides some optimizations related to attaching to, and indexing into, file-backed matrices with dimnames. Additionally, the package provides a "BigMatrixFactor" class, a file-backed matrix with factor properties.

library(bigmemoryExtras)
data.file = file.path(tempdir(),"bigmat","ds")
x = matrix(1:9,ncol=3,dimnames=list(letters[1:3],LETTERS[1:3]))
ds = BigMatrix(x,data.file)
ds[,1] = 3:1
ds[,1]

Re-attaching to on-disk data as necessary

When a big.matrix object is attached to it's on-disk data, an external pointer is used to connect the R object to a C++ data structure. When a big.matrix object is not attached, like when it is loaded from an RData file, this pointer is nil. Any access to this nil pointer will crash R. The bigmemoryExtras package provides a BigMatrix class that prevents such a crash by controlling access to the external pointer. Additionally, BigMatrix objects remember the location of their on-disk components and automatically re-attach themselves as necessary.

This kind of thing would be helpful if you, for example, chose to save your new BigMatrix object to disk for later use. You might save your object using R's built in save or saveRDS functions.

ds$backingfile
saveRDS(ds,file=file.path(tempdir(),"foo.rds"))
new.ds = readRDS(file=file.path(tempdir(),"foo.rds"))
new.ds[1:2,2:3]

S4 Style Access

The BigMatrix class uses R's Reference Class system. Any change to the matrix portion of the data has on-disk side effects, so it seems natural that any other changes to the object should have the same behavior. In order to give BigMatrix the same API as a base matrix or big.matrix class, certain S4-style methods are provided. ReferenceClass objects are relatively new to R and unfamiliar to many users, so you may want to review the ReferenceClasses help page.

nrow(ds)
ds$nrow()
ncol(ds)
ds$ncol()
dim(ds)
ds$dim()
dimnames(ds)
ds$dimnames()
length(ds)
ds$length()

BigMatrixFactor

The bigmemoryExtras package adds a ``BigMatrixFactor'' class to provide a means to store large matrices of characters. On the file system, these are stored as the C type char or int (8 or 32 bits), depending on the number of levels in the factor. Subsetting a BigMatrixFactor returns a factor. If more than one column is returned, the returned object is a factor matrix.

data.file = file.path(tempdir(),"bigmat","fs")
x = matrix( c(rep("AA",5),rep("BB",4)) ,ncol=3,dimnames=list(letters[1:3],LETTERS[1:3]))
fs = BigMatrixFactor(x,data.file,levels=c("AA","BB"))
fs[,]
as(fs,"matrix")
fs$levels
levels(fs)
fs[, 2]
fs[, 2:3]

Use with GenomicRanges and SummarizedExperiment-derived Classes

Either class can be used as an assay in the assays slot of the GenomicRanges SummarizedExperiment-derived classes. We provide utility functions to deal with relocated BigMatrix in such a container.

library(GenomicRanges)
se = SummarizedExperiment(assays=list(a=ds, b=fs))
assays(se)[["a"]]
new.dir = file.path(tempdir(),"newbigmat")
dir.create(new.dir,showWarnings=FALSE)
file.copy(ds$backingfile, new.dir)
file.copy(fs$backingfile, new.dir)
assays(se) = updateBackingfiles(assays(se), new.dir)
assays(se)[["b"]]$backingfile

Use with Biobase and eSet-derived Classes

We are phasing out Biobase and eSet in favor of GenomicRanges and SummarizedExperiment, but in the mean time ...

Either class can be used as an assayDataElement in the assayData slot of the familiar BioConductor eSet-derived classes. We provide utility functions to deal with relocated BigMatrix files.

library(Biobase)
eset = ExpressionSet()
data.file = file.path(tempdir(),"bigmat","ds")
x = matrix(1:9,ncol=3,dimnames=list(letters[1:3],LETTERS[1:3]))
ds = BigMatrix(x,data.file)
assayDataElement(eset,"exprs") = ds
exprs(eset)[1:2,2:3]

new.dir = file.path(tempdir(),"newbigmat")
dir.create(new.dir,showWarnings=FALSE)
file.copy(ds$backingfile, new.dir)
assayData(eset) = updateBackingfiles(assayData(eset), new.dir)
assayDataElement(eset,"exprs")$backingfile


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bigmemoryExtras documentation built on Nov. 1, 2018, 3:44 a.m.