Connecting Bioconductor to other bioinformatics tools using Rcwl - Application in scRNA-seq data

Instructor(s) name(s) and contact information

• Qian Liu (Qian.Liu@roswellpark.org) twitter
• Qiang Hu (Qiang.Hu@roswellpark.org) twitter
• Slack channel: community-bioc/#rcwl

Workshop Description

This workshop introduces the Bioconductor toolchain for usage and development of reproducible bioinformatics pipelines using packages of Rcwl and RcwlPipelines. The Common Workflow Language (CWL) is an open standard for development of data analysis workflows that is portable and scalable across different tools and working environments.

Rcwl provides a simple way to wrap command line tools and build CWL data analysis pipelines programmatically within R. It increases the ease of usage, development, and maintenance of CWL pipelines, and furthermore offers higher performance by intuitively supporting parallel work with high performance computing (HPC). More than a hundred of pre-built and tested CWL tool/pipeline recipes are included in RcwlPipelines. These tools and pipelines are highly modularized for easy customization of complex bioinformatics analysis.

Here we included a scRNAseq preprocessing pipeline which uses STARsolo for alignment and quantification, and DropletUtils for filtering raw gene-barcode matrix and removing empty droplets. This pipeline demonstrates the typical use case of our packages.

Workshop materials can be found here: http://rcwl.org/Rcwl_scRNAseq/

Docker instructions:

In order to run the workshop successfully, users need to do either of the following:

1. Install docker.
2. Install needed tools: STAR.

Users also need to install the following packages:

BiocManager::install(c("rworkflow/Rcwl", "rcwlwork/RcwlPipelines", 
	                "git2r", "DropletUtils", "BiocParallel"))