N-of-one differential gene expression without control samples using a deep generative model
Abstract Differential analysis of bulk RNA-seq data often suffers from lack of good controls. Here, we present a generative model that replaces controls, trained solely on healthy tissues. The unsupervised model learns a low-dimensional representation and can identify the closest normal representati...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
BMC
2023-11-01
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Series: | Genome Biology |
Subjects: | |
Online Access: | https://doi.org/10.1186/s13059-023-03104-7 |