CellBench

CellBench provides an R/Bioconductor framework to benchmark single-cell RNA sequencing (scRNA-seq) analysis methods by organizing and comparing multi-step pipelines and quantifying performance for tasks such as normalization, imputation, clustering, trajectory analysis, and data integration.

Key Features:

• Pipeline Management: Provides a framework to organize and evaluate multi-step analysis pipelines and method combinations programmatically.
• Automated Method Combinations: Automates execution of diverse combinations of analysis methods to enable exhaustive benchmarking across methods and parameterizations.
• Performance Metrics: Computes comprehensive performance metrics from datasets with known ground truth for tasks including normalization, imputation, clustering, trajectory analysis, and data integration.
• Time Measurement Facilities: Includes utilities to measure running time of method combinations for assessment of computational efficiency.
• Output Compatibility: Produces results in tabular formats compatible with tidyverse R packages for downstream summarization and visualization.
• SingleCellExperiment Support: Supports sampling and filtering of SingleCellExperiment objects for use as input in benchmarking workflows.
• Versatility: Applicable to benchmarking other bioinformatics tasks beyond scRNA-seq through its flexible method-combination framework.

Scientific Applications:

• Method Comparison: Systematic comparison and ranking of scRNA-seq analysis methods across pipeline steps.
• Task Evaluation: Quantitative evaluation of normalization, imputation, clustering, trajectory analysis, and data integration approaches.
• Best Practices Development: Support for establishing best-practice recommendations and consensus on scRNA-seq analysis workflows via reproducible benchmarking.
• Cross-domain Benchmarking: Extension of benchmarking approaches to other bioinformatics analysis tasks by reusing the combinatorial framework.

Methodology:

Uses a task-centric combinatorial approach; supports sampling and filtering of SingleCellExperiment objects; constructs lists of functions with varying parameters for multithreaded evaluation; and records running time and tabular results for downstream analysis.