May 16, 2020 · The aim of using a VAE is to capture the joint distribution of multivariate data such as gene expression profiles. Since our method is ...
Aug 15, 2020 · We propose a novel method based on variational auto-encoders (VAEs) for analysis of single-cell RNA sequencing (scRNA-seq) data.
This data set contains gene expression counts for samples of human cells from 51 tissue sites and two cell lines. We collate cell samples from similar tissue ...
Table S2: Test metrics for two of the purified immune cells data sets using the 800 most varying genes. PBMC. PBMC-T. Model. Likelihood function. Ltest. Rtest.
May 16, 2018 · Abstract. We propose a novel variational auto-encoder-based method for analysis of single-cell RNA sequencing (scRNA-seq) data.
May 16, 2018 · Results: We propose a novel method based on variational auto-encoders (VAEs) for analysis of single-cell RNA sequencing (scRNA-seq) data. It ...
scVAE: variational auto-encoders for single-cell gene expression data Available Online. Send to. QR. Mendeley. Export BibTeX. Export RIS. RefWorks. EndNote.
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We propose a novel method based on variational auto-encoders (VAEs) for analysis of single-cell RNA sequencing (scRNA-seq) data.
scVAE is a command-line tool for modelling single-cell transcript counts using variational auto-encoders. Install scVAE using pip for Python 3.6 and 3.7:.
Abstract Motivation Models for analysing and making relevant biological inferences from massive amounts of complex single-cell transcriptomic data typically ...