In bioinfocz/scdrake: A pipeline for droplet-based single-cell RNA-seq data secondary analysis implemented in the drake Make-like toolkit for R language

Because {drake} knows the inner relationships between targets in your plan, it also knows which targets are independent of each other, and thus, can be run concurrently. This is called implicit parallelism, and to fully utilize this important feature, you just need to modify config/pipeline.yaml by setting DRAKE_PARALLELISM to either:

• "future": uses the {future} as the backend. This backend should work by simply installing the {future} package.
• Install by BiocManager::install(c("future", "future.callr"))
• "clustermq": uses the {clustermq} as the backend. This is faster than "future", but besides the {clustermq} package it also requires the ZeroMQ library to be installed on your system.
• A specific version of the {clustermq} package is needed and can be installed with remotes::install_version("clustermq", version = "0.8.8") (you might need BiocManager::install("remotes")).
• {clustermq} also supports HPC cluster schedulers, see here for more details.

If you have installed {scdrake} from the renv.lock file or you are using the Docker image, then these two packages above are always installed.

For a general overview of {drake} parallelism see https://books.ropensci.org/drake/hpc.html

bioinfocz/scdrake documentation built on Sept. 19, 2024, 4:43 p.m.