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bioRxiv · 10.1101/025437

OEFinder: A user interface to identify and visualize ordering effects in single-cell RNA-seq data

Ning Leng·Jeea Choi·Li-Fang Chu·James Thomson·Christina Kendziorski·Ron Stewart
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Abstract

A recent paper identified an artifact in multiple single-cell RNA-seq (scRNA-seq) data sets generated by the Fluidigm C1 platform. Specifically, Leng* et al. showed significantly increased gene expression in cells captured from sites with small or large plate output IDs. We refer to this artifact as an ordering effect (OE). Including OE genes in downstream analyses could lead to biased results. To address this problem, we developed a statistical method and software called OEFinder to identify a sorted list of OE genes. OEFinder is available as an R package along with user-friendly graphical interface implementations that allows users to check for potential artifacts in scRNA-seq data generated by the Fluidigm C1 platform.\n\nAvailability and ImplementationOEFinder is freely available at https://github.com/lengning/OEFinder\n\nContactrstewart@morgridge.org

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Ning Leng, Jeea Choi, Li-Fang Chu, James Thomson, Christina Kendziorski, Ron Stewart. 2015-08-25. OEFinder: A user interface to identify and visualize ordering effects in single-cell RNA-seq data. https://doi.org/10.1101/025437

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