The 'SingleCellExperiment' logo + The 'futurize' hexlogo = The 'future' logo
The **futurize** package allows you to easily turn sequential code into parallel code by piping the sequential code to the `futurize()` function. Easy! # TL;DR ```r library(futurize) plan(multisession) library(SingleCellExperiment) library(scuttle) result <- applySCE(sce, perFeatureQCMetrics) |> futurize() ``` # Introduction This vignette demonstrates how to use this approach to parallelize the **[SingleCellExperiment]** functions. The **[SingleCellExperiment]** Bioconductor package defines the `SingleCellExperiment` class for storing single-cell genomics data, including alternative experiments (e.g. spike-in transcripts, antibody tags). The `applySCE()` function applies a given function to the main experiment and each alternative experiment, passing additional arguments such as `BPPARAM` via `...` to enable parallelization of the applied function. ## Example: Computing per-feature QC metrics in parallel The `applySCE()` function applies a function across the main experiment and its alternative experiments: ```r library(SingleCellExperiment) library(scuttle) # Simulate data sce <- mockSCE() result <- applySCE(sce, perFeatureQCMetrics) ``` Here `applySCE()` runs `perFeatureQCMetrics()` from the **[scuttle]** package sequentially on each experiment, but we can easily make it run in parallel by piping to `futurize()`: ```r library(futurize) result <- applySCE(sce, perFeatureQCMetrics) |> futurize() ``` It is actually not `SingleCellExperiment::applySCE()` that orchestrates the parallelization, but `scuttle::perFeatureQCMetrics()`, which hands of the parallelization to **[BiocParallel]** which in turn hands it of to futureverse. The above will distribute the work across the available parallel workers, given that we have set up parallel workers, e.g. ```r plan(multisession) ``` The built-in `multisession` backend parallelizes on your local computer and works on all operating systems. There are [other parallel backends] to choose from, including alternatives to parallelize locally as well as distributed across remote machines, e.g. ```r plan(future.mirai::mirai_multisession) ``` and ```r plan(future.batchtools::batchtools_slurm) ``` # Supported Functions The following **SingleCellExperiment** functions are supported by `futurize()`: * `applySCE()` [BiocParallel]: https://bioconductor.org/packages/BiocParallel/ [SingleCellExperiment]: https://bioconductor.org/packages/SingleCellExperiment/ [scuttle]: https://bioconductor.org/packages/scuttle/ [other parallel backends]: https://www.futureverse.org/backends.html