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

Summary: A recent article identified an artifact in multiple single-cell RNA-seq (scRNA-seq) datasets 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 ar...

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Detalles Bibliográficos
Autores principales: Leng, Ning, Choi, Jeea, Chu, Li-Fang, Thomson, James A., Kendziorski, Christina, Stewart, Ron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4848403/
https://www.ncbi.nlm.nih.gov/pubmed/26743507
http://dx.doi.org/10.1093/bioinformatics/btw004
Descripción
Sumario:Summary: A recent article identified an artifact in multiple single-cell RNA-seq (scRNA-seq) datasets 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 which allows users to check for potential artifacts in scRNA-seq data generated by the Fluidigm C1 platform. Availability and implementation: OEFinder is freely available at https://github.com/lengning/OEFinder Contact: rstewart@morgridge.org or lengning1@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.