AI/ML

Data denoising with transfer learning in single-cell transcriptomics.

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Data denoising with transfer learning in single-cell transcriptomics.

Nat Methods. 2019 09;16(9):875-878

Authors: Wang J, Agarwal D, Huang M, Hu G, Zhou Z, Ye C, Zhang NR

Abstract
Single-cell RNA sequencing (scRNA-seq) data are noisy and sparse. Here, we show that transfer learning across datasets remarkably improves data quality. By coupling a deep autoencoder with a Bayesian model, SAVER-X extracts transferable gene-gene relationships across data from different labs, varying conditions and divergent species, to denoise new target datasets.

PMID: 31471617 [PubMed – indexed for MEDLINE]

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