Scaling up reproducible research for single-cell transcriptomics using MetaNeighbor.

Fischer, Stephan, Crow, Megan, Harris, Benjamin D, Gillis, Jesse (July 2021) Scaling up reproducible research for single-cell transcriptomics using MetaNeighbor. Nature Protocols. ISSN 1754-2189

DOI: 10.1038/s41596-021-00575-5


Single-cell RNA-sequencing data have significantly advanced the characterization of cell-type diversity and composition. However, cell-type definitions vary across data and analysis pipelines, raising concerns about cell-type validity and generalizability. With MetaNeighbor, we proposed an efficient and robust quantification of cell-type replicability that preserves dataset independence and is highly scalable compared to dataset integration. In this protocol, we show how MetaNeighbor can be used to characterize cell-type replicability by following a simple three-step procedure: gene filtering, neighbor voting and visualization. We show how these steps can be tailored to quantify cell-type replicability, determine gene sets that contribute to cell-type identity and pretrain a model on a reference taxonomy to rapidly assess newly generated data. The protocol is based on an open-source R package available from Bioconductor and GitHub, requires basic familiarity with Rstudio or the R command line and can typically be run in <5 min for millions of cells.

Item Type: Paper
Subjects: bioinformatics > computational biology
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > transcriptomes
CSHL Authors:
Communities: CSHL labs > Gillis Lab
School of Biological Sciences > Publications
SWORD Depositor: CSHL Elements
Depositing User: CSHL Elements
Date: 7 July 2021
Date Deposited: 09 Jul 2021 13:57
Last Modified: 31 May 2022 20:52
PMCID: PMC8826496

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