Ontology highlight
ABSTRACT:
SUBMITTER: Skinnider MA
PROVIDER: S-EPMC7610525 | biostudies-literature | 2021 Jan
REPOSITORIES: biostudies-literature
Skinnider Michael A MA Squair Jordan W JW Kathe Claudia C Anderson Mark A MA Gautier Matthieu M Matson Kaya J E KJE Milano Marco M Hutson Thomas H TH Barraud Quentin Q Phillips Aaron A AA Foster Leonard J LJ La Manno Gioele G Levine Ariel J AJ Courtine Grégoire G
Nature biotechnology 20200720 1
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 circuit ...[more]