VeloTree infers differentiation trees from RNA velocity fields by defining cell dissimilarity as the squared varifold distance between integral curves of the velocity field.
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A large benchmark finds traditional imputation methods for scRNA-seq data generally outperform deep learning ones, but numerical recovery does not reliably improve biological downstream analyses and no method wins across all settings.
A tractable estimator for functional KL divergence provides a coherent way to compare trajectory inference methods and reveal discrepancies in inferred dynamics from snapshot data.
citing papers explorer
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VeloTree: Inferring single-cell trajectories from RNA velocity fields with varifold distances
VeloTree infers differentiation trees from RNA velocity fields by defining cell dissimilarity as the squared varifold distance between integral curves of the velocity field.
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A Large-Scale Comparative Analysis of Imputation Methods for Single-Cell RNA Sequencing Data
A large benchmark finds traditional imputation methods for scRNA-seq data generally outperform deep learning ones, but numerical recovery does not reliably improve biological downstream analyses and no method wins across all settings.
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Relative Entropy Estimation in Function Space: Theory and Applications to Trajectory Inference
A tractable estimator for functional KL divergence provides a coherent way to compare trajectory inference methods and reveal discrepancies in inferred dynamics from snapshot data.