CellBench: R/Bioconductor software for comparing single-cell RNA-seq analysis methods
Journal Title
Publication Type
Journal Article in press
MOTIVATION: Bioinformatic analysis of f gene expression data is a rapidly evolving field. Hundreds of bespoke methods have been developed in the past few years to deal with various aspects of single-cell analysis and consensus on the most appropriate methods to use under different settings is still emerging. Benchmarking the many methods is therefore of critical importance and since analysis of single-cell data usually involves multi-step pipelines, effective evaluation of pipelines involving different combinations of methods is required. Current benchmarks of single-cell methods are mostly implemented with ad-hoc code that is often difficult to reproduce or extend, and exhaustive manually coding of the many combinations is infeasible in most instances. Therefore, new software is needed to manage pipeline benchmark. RESULTS: The CellBench R software method comparisons in either a task-centric, or combinatorial way to allow pipelines of methods to be evaluated in an effective manner. CellBench automatically runs combinations of methods, provides facilities for measuring running time and delivers output in tabular form which is highly compatible with tidyverse R packages for summary and visualisation. Our software has enabled comprehensive benchmarking of single-cell RNA-seq normaliation, imputation, clustering, trajectory analysis and data integration methods using various performance metrics obtained from data with available ground-truth. CellBench is amenable to benchmarking other bioinformatics analysis tasks. SOFTWARE AVAILABILITY: available from https://bioconductor.org/packages/CellBench.
Oxford Academic
WEHI Research Division(s)
Epigenetics And Development
PubMed ID
Open Access at Publisher's Site
NHMRC Grants
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Creation Date: 2019-12-05 01:26:21
Last Modified: 2020-02-11 09:21:46
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