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A novel metric reveals previously unrecognized distortion in the analysis of scRNA-seq data
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Tumor Cell Biodiversity Drives Microenvironmental Reprogramming in Liver Cancer
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A Single-Cell Transcriptome Atlas of the Aging Drosophila Brain
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Manifold learning-based methods for analyzing single-cell RNA-sequencing data
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Modeling wine preferences by data mining from physicochemical properties
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On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality
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Analysis of a complex of statistical variables into principal components.
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A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex
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Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression
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PROSSTT: probabilistic simulation of single-cell RNA-seq data for complex differentiation processes
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Nonlinear Dimensionality Reduction by Locally Linear Embedding
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Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding
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Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis
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High-Throughput Genomic Data in Systematics and Phylogenetics
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Splatter: simulation of single-cell RNA sequencing data
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SCANPY: large-scale single-cell gene expression data analysis
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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