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pipeComp, a general framework for the evaluation of computational pipelines, reveals performant single-cell RNA-seq preprocessing tools

View ORCID ProfilePierre-Luc Germain, View ORCID ProfileAnthony Sonrel, View ORCID ProfileMark D Robinson
doi: https://doi.org/10.1101/2020.02.02.930578
Pierre-Luc Germain
Eidgenoessische Technische Hochschule Zuerich;
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  • For correspondence: germain@hifo.uzh.ch
Anthony Sonrel
University of Zurich
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  • For correspondence: anthony.sonrel@uzh.ch
Mark D Robinson
University of Zurich
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  • For correspondence: mark.robinson@imls.uzh.ch
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Abstract

The massive growth of single-cell RNA-sequencing (scRNAseq) and methods for its analysis still lacks sufficient and up-to-date benchmarks that would guide analytical choices. Moreover, current studies are often focused on isolated steps of the process. Here, we present a flexible R framework for pipeline comparison with multi-level evaluation metrics and apply it to the benchmark of scRNAseq analysis pipelines using datasets with known cell identities. We evaluate common steps of such analyses, including filtering, doublet detection (suggesting a new R package, scDblFinder), normalization, feature selection, denoising, dimensionality reduction and clustering. On the basis of these analyses, we make a number of concrete recommendations about analysis choices. The evaluation framework, pipeComp, has been implemented so as to easily integrate any other step or tool, allowing extensible benchmarks and easy application to other fields (https://github.com/plger/pipeComp).

Footnotes

  • https://github.com/plger/pipeComp

  • https://github.com/markrobinsonuzh/scRNA_pipelines_paper

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted February 02, 2020.
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pipeComp, a general framework for the evaluation of computational pipelines, reveals performant single-cell RNA-seq preprocessing tools
Pierre-Luc Germain, Anthony Sonrel, Mark D Robinson
bioRxiv 2020.02.02.930578; doi: https://doi.org/10.1101/2020.02.02.930578
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pipeComp, a general framework for the evaluation of computational pipelines, reveals performant single-cell RNA-seq preprocessing tools
Pierre-Luc Germain, Anthony Sonrel, Mark D Robinson
bioRxiv 2020.02.02.930578; doi: https://doi.org/10.1101/2020.02.02.930578

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