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Visualizing Structure and Transitions for Biological Data Exploration

65 Pages Posted: 10 Apr 2018 Sneak Peek Status: Review Complete

See all articles by Kevin R. Moon

Kevin R. Moon

Yale University - Department of Genetics

David van Dijk

Yale University - Department of Genetics

Zheng Wang

Yale University - Yale Stem Cell Center

Daniel Burkhardt

Yale University - Department of Genetics

William S. Chen

Yale University - Department of Genetics

Kristina Yim

Yale University - Department of Genetics

Antonia van den Elzen

Yale University - Department of Genetics

Matthew J. Hirn

Michigan State University - Department of Mathematics

Ronald R. Coifman

Yale University - Applied Mathematics Program

Natalia B. Ivanova

Yale University - Yale Stem Cell Center

Guy Wolf

Yale University - Applied Mathematics Program

Smita Krishnaswamy

Yale University - Department of Genetics

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Abstract

With the advent of high-throughput technologies measuring high-dimensional biological data, there is a pressing need for visualization tools that reveal data structure and emergent patterns in an intuitive form. We present PHATE, an unsupervised visualization method that captures both local and global non-linear structure in data by preserving informational distance between data points. PHATE reveals a range of patterns in data including continual progressions, branches, and clusters without imposing any prior assumptions on the latent data structure. We apply PHATE on a wide variety of datasets, including CyTOF, single-cell RNA-sequencing (scRNA-seq), Hi-C, and gut microbiome data and show its effectiveness in generating new insights into the underlying systems. We apply and experimentally validate PHATE using a newly generated scRNA-seq dataset of human germ layer differentiation in which PHATE reveals a dynamic picture of the main developmental branches in unparalleled detail.

Suggested Citation

Moon, Kevin R. and Dijk, David van and Wang, Zheng and Burkhardt, Daniel and Chen, William S. and Yim, Kristina and Elzen, Antonia van den and Hirn, Matthew J. and Coifman, Ronald R. and Ivanova, Natalia B. and Wolf, Guy and Krishnaswamy, Smita, Visualizing Structure and Transitions for Biological Data Exploration (2018). Available at SSRN: https://ssrn.com/abstract=3155891 or http://dx.doi.org/10.2139/ssrn.3155891
This is a paper under consideration at Cell Press and has not been peer-reviewed.

Kevin R. Moon

Yale University - Department of Genetics

333 Cedar Street
New Haven, CT 06520
United States

David van Dijk

Yale University - Department of Genetics

333 Cedar Street
New Haven, CT 06520
United States

Zheng Wang

Yale University - Yale Stem Cell Center

PO Box 208073
New Haven, CT 06520
United States

Daniel Burkhardt

Yale University - Department of Genetics

333 Cedar Street
New Haven, CT 06520
United States

William S. Chen

Yale University - Department of Genetics

333 Cedar Street
New Haven, CT 06520
United States

Kristina Yim

Yale University - Department of Genetics

333 Cedar Street
New Haven, CT 06520
United States

Antonia van den Elzen

Yale University - Department of Genetics

333 Cedar Street
New Haven, CT 06520
United States

Matthew J. Hirn

Michigan State University - Department of Mathematics

619 Red Cedar Road
East Lansing, MI 48824
United States

Ronald R. Coifman

Yale University - Applied Mathematics Program

51 Prospect Street
New Haven, CT 06511
United States

Natalia B. Ivanova

Yale University - Yale Stem Cell Center ( email )

PO Box 208073
New Haven, CT 06520
United States

Guy Wolf

Yale University - Applied Mathematics Program

51 Prospect Street
New Haven, CT 06511
United States

Smita Krishnaswamy (Contact Author)

Yale University - Department of Genetics ( email )

333 Cedar Street
New Haven, CT 06520
United States

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