BatchBench

BatchBench provides a Nextflow workflow to compare and evaluate batch effect correction methods for single-cell RNA sequencing (scRNA-Seq) data.

Key Features:

• Nextflow workflow: Implements the pipeline using Nextflow for workflow management and reproducible execution.
• Batch correction methods: Supports evaluation of eight different batch effect correction methods with distinct methodological approaches.
• Data type: Operates specifically on single-cell RNA sequencing (scRNA-Seq) data.
• Modularity: Provides a modular and flexible pipeline architecture for systematic comparison of batch correction methods.
• Benchmarking: Assesses method performance and computational demands across well-studied datasets.
• Execution control: Executed via a bash script with options to specify profiles, data directories, and output directories, and includes a -resume command-line option.
• Reporting: Generates detailed execution reports, timelines, and flowcharts via Nextflow and stores them in the specified output directory.

Scientific Applications:

• Dataset integration: Comparing and integrating newly generated and publicly available scRNA-Seq datasets to mitigate non-biological batch effects.
• Method benchmarking: Systematic evaluation of batch correction methods to quantify performance and computational requirements.
• Method selection: Guiding selection of appropriate batch effect correction approaches for specific single-cell genomics studies.
• Reproducibility assessment: Supporting reproducibility and reliability assessments in single-cell RNA-Seq analyses.

Methodology:

Implemented as a Nextflow workflow executed via a bash script that accepts profiles, data directories, and output directories, supports a -resume option, evaluates eight batch correction methods on scRNA-Seq datasets, and generates Nextflow execution reports, timelines, and flowcharts stored in the output directory.