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---
title: "Using DelayedMatrix with MultiAssayExperiment"
author: "MultiAssay Special Interest Group"
date: "`r format(Sys.time(), '%B %d, %Y')`"
vignette: >
%\VignetteEngine{knitr::rmarkdown}
%\VignetteIndexEntry{HDF5Array and MultiAssayExperiment}
%\VignetteEncoding{UTF-8}
output:
BiocStyle::html_document:
number_sections: yes
toc: yes
---
# Integrating an HDF5 backend for MultiAssayExperiment
## Dependencies
```{r,include=TRUE,results="hide",message=FALSE,warning=FALSE}
library(MultiAssayExperiment)
library(HDF5Array)
library(SummarizedExperiment)
```
## HDF5Array and DelayedArray Constructor
The `HDF5Array` package provides an on-disk representation of large datasets
without the need to load them into memory. Convenient lazy evaluation
operations allow the user to manipulate such large data files based on
metadata. The `DelayedMatrix` class in the `DelayedArray` package provides a
way to connect to a large matrix that is stored on disk.
First, we create a small matrix for constructing the `DelayedMatrix` class.
```{r}
smallMatrix <- matrix(rnorm(10e5), ncol = 20)
```
We add rownames and column names to the matrix object for compatibility with
the `MultiAssayExperiment` representation.
```{r}
rownames(smallMatrix) <- paste0("GENE", seq_len(nrow(smallMatrix)))
colnames(smallMatrix) <- paste0("SampleID", seq_len(ncol(smallMatrix)))
```
Here we use the `DelayedArray` constructor function to create a
`DelayedMatrix` object.
```{r}
smallMatrix <- DelayedArray(smallMatrix)
class(smallMatrix)
# show method
smallMatrix
dim(smallMatrix)
```
## Writing to a file with dimnames
Finally, the `rhdf5` package stores `dimnames` in a standard location.
In order to make use of this functionality, we would use `writeHDF5Array`
with the `with.dimnames` argument:
```{r}
testh5 <- tempfile(fileext = ".h5")
writeHDF5Array(smallMatrix, filepath = testh5, name = "smallMatrix",
with.dimnames = TRUE)
```
To see the file structure we use `h5ls`:
```{r}
h5ls(testh5)
```
## Importing HDF5 files
Note that a large matrix from an HDF5 file can also be loaded using the
`HDF5ArraySeed` and `DelayedArray` functions.
```{r}
hdf5Data <- HDF5ArraySeed(file = testh5, name = "smallMatrix")
newDelayedMatrix <- DelayedArray(hdf5Data)
class(newDelayedMatrix)
newDelayedMatrix
```
## Using a `DelayedMatrix` with `MultiAssayExperiment`
A `DelayedMatrix` alone conforms to the `MultiAssayExperiment` API requirements.
Shown below, the `DelayedMatrix` can be put into a named `list` and passed into
the `MultiAssayExperiment` constructor function.
```{r}
HDF5MAE <- MultiAssayExperiment(experiments = list(smallMatrix = smallMatrix))
sampleMap(HDF5MAE)
colData(HDF5MAE)
```
### `SummarizedExperiment` with `DelayedMatrix` backend
A more information rich `DelayedMatrix` can be created when used in conjunction
with the `SummarizedExperiment` class and it can even include `rowRanges`.
The flexibility of the `MultiAssayExperiment` API supports classes with
minimal requirements. Additionally, this `SummarizedExperiment` with the
`DelayedMatrix` backend can be part of a bigger `MultiAssayExperiment` object.
Below is a minimal example of how this would work:
```{r}
HDF5SE <- SummarizedExperiment(assays = smallMatrix)
assay(HDF5SE)
MultiAssayExperiment(list(HDF5SE = HDF5SE))
```
Additional scenarios are currently in development where an `HDF5Matrix` is
hosted remotely. Many opportunities exist when considering on-disk and off-disk
representations of data with `MultiAssayExperiment`.
# Session info
```{r}
sessionInfo()
```
|
