Journal article

CellBench: R/Bioconductor software for comparing single-cell RNA-seq analysis methods

Shian Su, Luyi Tian, Xueyi Dong, Peter F Hickey, Saskia Freytag, Matthew E Ritchie

Bioinformatics | OXFORD UNIV PRESS | Published : 2020

Abstract

MOTIVATION: Bioinformatic analysis of single-cell 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 ..

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Grants

Awarded by National Health and Medical Research Council (NHMRC)


Awarded by Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation


Funding Acknowledgements

This project was supported by National Health and Medical Research Council (NHMRC) Project Grants (GNT1143163 and GNT1124812 to MER) and Career Development Fellowship (GNT1104924 to MER), the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation (grant numbers 2018-182819 and 2019-002443 to MER), a Melbourne Research Scholarship to LT and Victorian State Government Operational Infrastructure Support and Australian Government NHMRC IRIISS.