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Cell Type Hierarchy Reconstruction via Reconciliation of Multi-resolution Cluster Tree
Minshi Peng, Brie Wamsley, Andrew Elkins, Daniel M Geschwind, Yuting Wei, Kathryn Roeder
doi: https://doi.org/10.1101/2021.02.06.430067
Minshi Peng
1Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Brie Wamsley
2Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
Andrew Elkins
2Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
Daniel M Geschwind
2Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
3Program in Neurobehavioral Genetics and Center for Autism Research and Treatment Semel Institute and Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
Yuting Wei
1Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Kathryn Roeder
1Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
4Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA

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Posted February 08, 2021.
Cell Type Hierarchy Reconstruction via Reconciliation of Multi-resolution Cluster Tree
Minshi Peng, Brie Wamsley, Andrew Elkins, Daniel M Geschwind, Yuting Wei, Kathryn Roeder
bioRxiv 2021.02.06.430067; doi: https://doi.org/10.1101/2021.02.06.430067
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