Nature Biotechnology , Published: 20 July 2020
Michael A. Skinnider, Jordan W. Squair, Claudia Kathe, Mark A. Anderson, Matthieu Gautier, Kaya J.E. Matson, Marco Milano, Thomas H. Hutson, Quentin Barraud, Aaron A. Phillips, Leonard J. Foster, Gioele La Manno, Ariel J. Levine, Grégoire Courtine
Abstract
We present a machine-learning method to prioritize the cell types most responsive to biological perturbations within high-dimensional single-cell data. We validate our method, Augur (https://github.com/neurorestore/Augur), on a compendium of single-cell RNA-seq, chromatin accessibility, and imaging transcriptomics datasets. We apply Augur to expose the neural circuits that enable walking after paralysis in response to spinal cord neurostimulation.