A model-based, unsupervised manifold learning method that factors complex cellular trajectories into interpretable bifurcating Gaussian processes of transcription.
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Updated
Jan 1, 2024 - R
A model-based, unsupervised manifold learning method that factors complex cellular trajectories into interpretable bifurcating Gaussian processes of transcription.
An R package implementing the Local Tangent Space Alignment manifold learning method.
Scripts and data for reproducing analysis in Miller et al. 2020
Computationally Efficient Learning of Statistical Manifolds
Co-Ranking matrix and derived methods to assess the quality of dimensionality reductions
A computational method to rank and infer drug-responsive cell population towards in-silico drug perturbation using a target-perturbed gene regulatory network (tpGRN) for single-cell transcriptomic data
Dimension Reduction and Estimation Methods
A Framework for Dimensionality Reduction in R
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