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(scater) sce <- scuttle::logNormCounts(sce) sce <- runPCA(sce) |> futurize() sce <- runUMAP(sce) |> futurize() ``` # Introduction This vignette demonstrates how to use this approach to parallelize the **[scater]** functions. The **[scater]** Bioconductor package provides tools for single-cell RNA-seq data analysis, including dimensionality reduction methods such as PCA, t-SNE, and UMAP, which can be parallelized across cells. ## Example: Running PCA in parallel The `runPCA()` function performs PCA on a `SingleCellExperiment` object: ```r library(scater) # Simulate data set.seed(42) n_genes <- 200L n_cells <- 100L counts <- matrix( rpois(n_genes * n_cells, lambda = 10), nrow = n_genes, ncol = n_cells, dimnames = list( paste0("gene", seq_len(n_genes)), paste0("cell", seq_len(n_cells)) ) ) sce <- SingleCellExperiment::SingleCellExperiment( assays = list(counts = counts) ) sce <- scuttle::logNormCounts(sce) sce <- runPCA(sce) ``` Here `runPCA()` runs sequentially, but we can easily make it run in parallel by piping to `futurize()`: ```r library(futurize) sce <- runPCA(sce) |> futurize() ``` This 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 **scater** functions are supported by `futurize()`: * `calculatePCA()` * `calculateTSNE()` * `calculateUMAP()` * `runPCA()` * `runTSNE()` * `runUMAP()` * `runColDataPCA()` * `nexprs()` * `getVarianceExplained()` * `plotRLE()` [scater]: https://bioconductor.org/packages/scater/ [other parallel backends]: https://www.futureverse.org/backends.html