Single-cell RNA-sequencing (scRNA-seq) is a transformative technology, allowing global transcriptomes of individual cells to be profiled with high accuracy. An essential task in scRNA-seq data analysis is the identification of cell types from complex samples or tissues profiled in an ...
Read More »Data denoising with transfer learning in single-cell transcriptomics
Single-cell RNA sequencing (scRNA-seq) data are noisy and sparse. Here, UPENN researchers show that transfer learning across datasets remarkably improves data quality. By coupling a deep autoencoder with a Bayesian model, SAVER-X extracts...
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