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      Bifurcation analysis of single-cell gene expression data reveals epigenetic landscape.

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          Abstract

          We present single-cell clustering using bifurcation analysis (SCUBA), a novel computational method for extracting lineage relationships from single-cell gene expression data and modeling the dynamic changes associated with cell differentiation. SCUBA draws techniques from nonlinear dynamics and stochastic differential equation theories, providing a systematic framework for modeling complex processes involving multilineage specifications. By applying SCUBA to analyze two complementary, publicly available datasets we successfully reconstructed the cellular hierarchy during early development of mouse embryos, modeled the dynamic changes in gene expression patterns, and predicted the effects of perturbing key transcriptional regulators on inducing lineage biases. The results were robust with respect to experimental platform differences between RT-PCR and RNA sequencing. We selectively tested our predictions in Nanog mutants and found good agreement between SCUBA predictions and the experimental data. We further extended the utility of SCUBA by developing a method to reconstruct missing temporal-order information from a typical single-cell dataset. Analysis of a hematopoietic dataset suggests that our method is effective for reconstructing gene expression dynamics during human B-cell development. In summary, SCUBA provides a useful single-cell data analysis tool that is well-suited for the investigation of developmental processes.

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          Author and article information

          Journal
          Proc. Natl. Acad. Sci. U.S.A.
          Proceedings of the National Academy of Sciences of the United States of America
          1091-6490
          0027-8424
          Dec 30 2014
          : 111
          : 52
          Affiliations
          [1 ] Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA 02115;
          [2 ] Department of Systems Biology, Harvard Medical School, Boston, MA 02115;
          [3 ] Division of Pediatric Hematology/Oncology, Boston Children's Hospital and Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Harvard Medical School, Boston, MA 02115;
          [4 ] Department of Biological Sciences, National University of Singapore and Genome Institute of Singapore, Singapore 138672; and.
          [5 ] Department of Genetics, La Trobe University, Melbourne, VIC 3086, Australia.
          [6 ] Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA 02115; gcyuan@jimmy.harvard.edu.
          Article
          1408993111
          10.1073/pnas.1408993111
          25512504
          fb6ee07f-b841-49e5-8629-b0a735cd1674
          History

          bifurcation,differentiation,gene expression,single cell
          bifurcation, differentiation, gene expression, single cell

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