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Optimal-Transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming
Authors:Geoffrey Schiebinger  Jian Shu  Marcin Tabaka  Brian Cleary  Vidya Subramanian  Aryeh Solomon  Joshua Gould  Siyan Liu  Stacie Lin  Peter Berube  Lia Lee  Jenny Chen  Justin Brumbaugh  Philippe Rigollet  Konrad Hochedlinger  Rudolf Jaenisch  Aviv Regev  Eric S Lander
Institution:1. Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA;2. Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA;3. Computational and Systems Biology Program, MIT, Cambridge, MA 02142, USA;4. Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA 02139, USA;5. Cancer Center, Massachusetts General Hospital, Boston, MA 02114, USA;6. Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;7. Department of Molecular Biology, Center for Regenerative Medicine and Cancer Center, Massachusetts General Hospital, Boston, MA 02114, USA;8. Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA;9. Harvard Stem Cell Institute, Cambridge, MA 02138, USA;10. Harvard Medical School, Boston, MA 02115, USA;11. MIT Center for Statistics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;12. Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;13. Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA;14. Department of Systems Biology Harvard Medical School, Boston, MA 02125, USA;15. Biochemistry Program, Wellesley College, Wellesley, MA 02481, USA
Abstract:
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  • Keywords:optimal-transport  reprogramming  scRNA-seq  trajectories  ancestors  descendants  development  regulation  paracrine interactions  iPSCs
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