pipeComp, a general framework for the evaluation of computational pipelines, reveals performant single cell RNA-seq preprocessing tools
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Date
2020
Publication Type
Journal Article
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yes
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Abstract
We present pipeComp (https://github.com/plger/pipeComp), a flexible R framework for pipeline comparison handling interactions between analysis steps and relying on multi-level evaluation metrics. We apply it to the benchmark of single-cell RNA-sequencing analysis pipelines using simulated and real datasets with known cell identities, covering common methods of filtering, doublet detection, normalization, feature selection, denoising, dimensionality reduction, and clustering. pipeComp can easily integrate any other step, tool, or evaluation metric, allowing extensible benchmarks and easy applications to other fields, as we demonstrate through a study of the impact of removal of unwanted variation on differential expression analysis.
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published
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Volume
21 (1)
Pages / Article No.
227
Publisher
BioMed Central
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Software
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Subject
Single-cell RNA sequencing (scRNAseq); Pipeline; Clustering; Normalization; Filtering; Benchmark