Article

Representational Learning from Healthy Multi-Tissue Human RNA-seq Data such that Latent Space Arithmetics Extracts Disease Modules

2023-10-05

Abstract excerpt

1 Developing computational analyses of transcriptomic data has dramatically improved our understanding of complex multifactorial diseases. However, such approaches are limited to small sample sets of disease-affected material, thus being sensitive to statistical biases and noise. Here, we ask if a variational autoencoder (VAE) trained on large groups of healthy, human RNA-seq data of multiple tissues can capture t...

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Literature Corpus work: a2a41626-ad5d-5e8b-b976-67013cf8faf8
DOI: 10.1101/2023.10.03.560661

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