Article

Deep-learning-based cell composition analysis from tissue expression profiles

2019-06-04

Abstract excerpt

We present Scaden, a deep neural network for cell deconvolution that uses gene expression information to infer the cellular composition of tissues. Scaden is trained on single cell RNA-seq data to engineer discriminative features that confer robustness to bias and noise, making complex data preprocessing and feature selection unnecessary. We demonstrate that Scaden outperforms existing deconvolution algorithms in...

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Literature Corpus work: 30d2c8ab-3e51-5c36-b518-1e1dcbad182e
DOI: 10.1101/659227

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