#36 scVI with Romain Lopez and Gabriel Misrachi

Описание: In this episode, we hear from Romain Lopez (https://people.eecs.berkeley.edu/~rom...) and Gabriel Misrachi (  / gabriel-misrachi  ) about
scVI—Single-cell Variational Inference.
scVI is a probabilistic model for single-cell gene expression data that
combines a hierarchical Bayesian model with deep neural networks encoding the
conditional distributions. scVI scales to over one million cells and can be
used for scRNA-seq normalization and batch effect removal, dimensionality
reduction, visualization, and differential expression. We also
discuss the recently implemented in scVI automatic hyperparameter selection
via Bayesian optimization.








Links:




• Deep generative modeling for single-cell transcriptomics (https://rdcu.be/bdHYQ) (Romain Lopez, Jeffrey Regier, Michael Cole, Michael I. Jordan, Nir Yosef)


• scVI on GitHub (https://github.com/YosefLab/scVI)


• Should we zero-inflate scVI? (https://yoseflab.github.io/2019/06/25...)


• Hyperparameter search for scVI (https://yoseflab.github.io/2019/07/05...)


• Droplet scRNA-seq is not zero inflated (Valentine Svensson) (http://www.nxn.se/valent/2017/11/16/d...)