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scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured

A pressing challenge in single-cell transcriptomics is to benchmark experimental protocols and computational methods. A solution is to use computational simulators, but existing simulators cannot simultaneously achieve three goals: preserving genes, capturing gene correlations, and generating any nu...

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Detalles Bibliográficos
Autores principales: Sun, Tianyi, Song, Dongyuan, Li, Wei Vivian, Li, Jingyi Jessica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8147071/
https://www.ncbi.nlm.nih.gov/pubmed/34034771
http://dx.doi.org/10.1186/s13059-021-02367-2
Descripción
Sumario:A pressing challenge in single-cell transcriptomics is to benchmark experimental protocols and computational methods. A solution is to use computational simulators, but existing simulators cannot simultaneously achieve three goals: preserving genes, capturing gene correlations, and generating any number of cells with varying sequencing depths. To fill this gap, we propose scDesign2, a transparent simulator that achieves all three goals and generates high-fidelity synthetic data for multiple single-cell gene expression count-based technologies. In particular, scDesign2 is advantageous in its transparent use of probabilistic models and its ability to capture gene correlations via copulas. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13059-021-02367-2).