Single-cell Assisted Deconvolutional Network
Scaden is a tool for bulk RNA-seq cell type deconvolutional that uses a deep neural network ensemble trained on artificial bulk data simulated with scRNA-seq datasets. This method was developed in the Genome Biology of Neurodegenerativ Diseases group at the DZNE Tübingen and the Medical Systems Biology group at the ZMNH. The main author is Kevin Menden.
A paper describing Scaden has been published in Science Advances: Deep-learning based cell composition analysis from tissue expression profiles
For information about how to install Scaden, go to the Installation section. Look in the Usage section for general help with Scaden usage. In the Datasets section you'll find a list of prepared training datasets. You can also have a look in the Blog section, where I summarize new features that are added to Scaden.