Nat Biotechnol, Jan 2021

Cell type prioritization in single-cell data

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


We present Augur, a method to prioritize the cell types most responsive to biological perturbations in single-cell data. Augur employs a machine-learning framework to quantify the separability of perturbed and unperturbed cells within a high-dimensional space. We validate our method on single-cell RNA sequencing, chromatin accessibility and imaging transcriptomics datasets, and show that Augur outperforms existing methods based on differential gene expression. Augur identified the neural circuits restoring locomotion in mice following spinal cord neurosti


Read the full text