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Cell type prioritization in single-cell data.

  • Skinnider MA Brain Mind Institute, Faculty of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. michael.skinnider@msl.ubc.ca.
  • Squair JW Brain Mind Institute, Faculty of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. jordan.squair@epfl.ch.
  • Kathe C Brain Mind Institute, Faculty of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
  • Anderson MA Brain Mind Institute, Faculty of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
  • Gautier M Brain Mind Institute, Faculty of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
  • Matson KJE Spinal Circuits and Plasticity Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA.
  • Milano M Brain Mind Institute, Faculty of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
  • Hutson TH Brain Mind Institute, Faculty of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
  • Barraud Q Brain Mind Institute, Faculty of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
  • Phillips AA Departments of Physiology and Pharmacology, Clinical Neurosciences, and Cardiac Sciences, Hotchkiss Brain Institute and Libin Cardiovascular Institute of Alberta, Cumming School of Medicine, University of Calgary, Alberta, Canada.
  • Foster LJ Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada.
  • La Manno G Brain Mind Institute, Faculty of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
  • Levine AJ Spinal Circuits and Plasticity Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA.
  • Courtine G Brain Mind Institute, Faculty of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. gregoire.courtine@epfl.ch.
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  • 2020-07-22
Published in:
  • Nature biotechnology. - 2020
Biotechnology
Molecular Medicine
Applied Microbiology and Biotechnology
Bioengineering
Biomedical Engineering
English 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 neurostimulation.
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  • English
Open access status
green
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https://sonar.ch/global/documents/102565
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