Ontology highlight
ABSTRACT:
SUBMITTER: Menden K
PROVIDER: S-EPMC7439569 | biostudies-literature | 2020 Jul
REPOSITORIES: biostudies-literature
Menden Kevin K Marouf Mohamed M Oller Sergio S Dalmia Anupriya A Magruder Daniel Sumner DS Kloiber Karin K Heutink Peter P Bonn Stefan S
Science advances 20200722 30
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 sequencing (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 both precision and robustness. A single trained network reliably d ...[more]