Interpretable factor models of single-cell RNA-seq via variational autoencoders.

Volume: 36, Issue: 11, Pages: 3418 - 3421
Published: Jun 1, 2020
Abstract
Motivation null Single-cell RNA-seq makes possible the investigation of variability in gene expression among cells, and dependence of variation on cell type. Statistical inference methods for such analyses must be scalable, and ideally interpretable. null Results null We present an approach based on a modification of a recently published highly scalable variational autoencoder framework that provides interpretability without sacrificing much...
Paper Details
Title
Interpretable factor models of single-cell RNA-seq via variational autoencoders.
Published Date
Jun 1, 2020
Volume
36
Issue
11
Pages
3418 - 3421
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