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bioRxiv · 10.1101/583013

A Systematic Evaluation of Single Cell RNA-Seq Analysis Pipelines

Vieth, B.·Parekh, S.·Ziegenhain, C.·Enard, W.·Hellmann, I.
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Abstract

The recent rapid spread of single cell RNA sequencing (scRNA-seq) methods has created a large variety of experimental and computational pipelines for which best practices have not been established, yet. Here, we use simulations based on five scRNA-seq library protocols in combination with nine realistic differential expression (DE) setups to systematically evaluate three mapping, four imputation, seven normalisation and four differential expression testing approaches resulting in[~] 3,000 pipelines, allowing us to also assess interactions among pipeline steps. We find that choices of normalisation and library preparation protocols have the biggest impact on scRNA-seq analyses. Specifically, we find that library preparation determines the ability to detect symmetric expression differences, while normalisation dominates pipeline performance in asymmetric DE-setups. Finally, we illustrate the importance of informed choices by showing that a good scRNA-seq pipeline can have the same impact on detecting a biological signal as quadrupling the sample size.

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Vieth, B., Parekh, S., Ziegenhain, C., Enard, W., Hellmann, I.. 2019-03-19. A Systematic Evaluation of Single Cell RNA-Seq Analysis Pipelines. https://doi.org/10.1101/583013

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