HDF5Array-class {HDF5Array} | R Documentation |
We provide 2 classes for representing a conventional (i.e. dense) HDF5 dataset as an array-like object in R:
HDF5Array: A high-level class that extends DelayedArray. All the operations available for DelayedArray objects work on HDF5Array objects.
HDF5ArraySeed: A low-level class for pointing to an HDF5 dataset. No operation can be performed directly on an HDF5ArraySeed object. It first needs to be wrapped in a DelayedArray object. An HDF5Array object is just an HDF5ArraySeed object wrapped in a DelayedArray object.
## Constructor functions: HDF5Array(filepath, name, type=NA) HDF5ArraySeed(filepath, name, type=NA)
filepath |
The path (as a single character string) to the HDF5 file where the dataset is located. |
name |
The name of the dataset in the HDF5 file. |
type |
|
An HDF5Array object for HDF5Array()
.
An HDF5ArraySeed object for HDF5ArraySeed()
.
The 1.3 Million Brain Cell Dataset and other datasets published by 10x Genomics use an HDF5-based sparse matrix representation instead of the conventional (i.e. dense) HDF5 representation.
If your dataset uses the conventional (i.e. dense) HDF5 representation,
use the HDF5Array()
constructor.
If your dataset uses the HDF5-based sparse matrix representation from
10x Genomics, use the TENxMatrix()
constructor.
TENxMatrix objects for representing 10x Genomics datasets as DelayedArray objects.
DelayedArray objects in the DelayedArray package.
writeHDF5Array
for writing an array-like object
to an HDF5 file.
HDF5-dump-management for controlling the location and physical properties of automatically created HDF5 datasets.
saveHDF5SummarizedExperiment
and
loadHDF5SummarizedExperiment
in this
package (the HDF5Array package) for saving/loading
an HDF5-based SummarizedExperiment
object to/from disk.
h5ls
in the rhdf5 package.
The rhdf5 package on top of which HDF5Array and HDF5ArraySeed objects are implemented.
## --------------------------------------------------------------------- ## CONSTRUCTION ## --------------------------------------------------------------------- library(rhdf5) library(h5vcData) tally_file <- system.file("extdata", "example.tally.hfs5", package="h5vcData") h5ls(tally_file) ## Pick up "Coverages" dataset for Human chromosome 16: cov0 <- HDF5Array(tally_file, "/ExampleStudy/16/Coverages") cov0 is(cov0, "DelayedArray") # TRUE ## --------------------------------------------------------------------- ## dim/dimnames ## --------------------------------------------------------------------- dim(cov0) dimnames(cov0) dimnames(cov0) <- list(paste0("s", 1:6), c("+", "-"), NULL) dimnames(cov0) ## --------------------------------------------------------------------- ## SLICING (A.K.A. SUBSETTING) ## --------------------------------------------------------------------- cov1 <- cov0[ , , 29000001:29000007] cov1 dim(cov1) as.array(cov1) stopifnot(identical(dim(as.array(cov1)), dim(cov1))) stopifnot(identical(dimnames(as.array(cov1)), dimnames(cov1))) cov2 <- cov0[ , "+", 29000001:29000007] cov2 as.matrix(cov2) ## --------------------------------------------------------------------- ## SummarizedExperiment OBJECTS WITH DELAYED ASSAYS ## --------------------------------------------------------------------- ## DelayedArray objects can be used inside a SummarizedExperiment object ## to hold the assay data and to delay operations on them. library(SummarizedExperiment) pcov <- cov0[ , 1, ] # coverage on plus strand mcov <- cov0[ , 2, ] # coverage on minus strand nrow(pcov) # nb of samples ncol(pcov) # length of Human chromosome 16 ## The convention for a SummarizedExperiment object is to have 1 column ## per sample so first we need to transpose 'pcov' and 'mcov': pcov <- t(pcov) mcov <- t(mcov) se <- SummarizedExperiment(list(pcov=pcov, mcov=mcov)) se stopifnot(validObject(se, complete=TRUE)) ## A GPos object can be used to represent the genomic positions along ## the dataset: gpos <- GPos(GRanges("16", IRanges(1, nrow(se)))) gpos rowRanges(se) <- gpos se stopifnot(validObject(se)) assays(se)$pcov assays(se)$mcov