期刊
NATURE BIOTECHNOLOGY
卷 39, 期 1, 页码 30-34出版社
NATURE PORTFOLIO
DOI: 10.1038/s41587-020-0605-1
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资金
- European Research Council [ERC-2015-CoG HOW2WALKAGAIN 682999]
- Swiss National Science Foundation [310030_185214, 310030_192558]
- Genome Canada
- Genome British Columbia [214PRO]
- Wings for Life
- Intramural Research Program of the NIH, NINDS
- WestGrid
- Canadian Institutes of Health Research (CIHR)
- Izaak Walton Killam Memorial Pre-Doctoral Fellowship
- Compute Canada
- BCRegMed Collaborative Research Travel Grant
- CIHR Banting postdoctoral fellowship
- Marie Skodowska-Curie individual fellowship [842578]
- SNF Ambizione fellowship [PZ00P3_185728]
- Morton Cure Paralysis Fund
- UBC Four Year Fellowship
- Vancouver Coastal Health-CIHR-UBC MD/PhD Studentship
- Brain Canada Hubert van Tol fellowship
- Swiss National Science Foundation (SNF) [310030_185214, PZ00P3_185728, 310030_192558] Funding Source: Swiss National Science Foundation (SNF)
The Augur method can effectively identify the cell types most responsive to biological perturbations in single-cell data, helping to explore the relationship between gene expression changes and biological functions.
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. The cell types affected by biological perturbations in complex tissues are uncovered by single-cell analysis.
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