Pediatric Sarcoma Data Forms a Unique Cluster Measured via the Earth Mover’s Distance

Yongxin Chen; Filemon Dela Cruz; Romeil Sandhu; Andrew L. Kung; Prabhjot Mundi; Joseph O. Deasy; Allen Tannenbaum

doi:10.1038/s41598-017-07551-8

Scientific Reports (Aug 2017)

Pediatric Sarcoma Data Forms a Unique Cluster Measured via the Earth Mover’s Distance

Yongxin Chen,
Filemon Dela Cruz,
Romeil Sandhu,
Andrew L. Kung,
Prabhjot Mundi,
Joseph O. Deasy,
Allen Tannenbaum

Affiliations

Yongxin Chen: Memorial Sloan Kettering Cancer Center, Department of Medical Physics
Filemon Dela Cruz: Memorial Sloan Kettering Cancer Center, Department of Pediatrics
Romeil Sandhu: Stony Brook University, Department of Biomedical Informatics
Andrew L. Kung: Memorial Sloan Kettering Cancer Center, Department of Pediatrics
Prabhjot Mundi: Columbia University, Department of Medical Oncology
Joseph O. Deasy: Memorial Sloan Kettering Cancer Center, Department of Medical Physics
Allen Tannenbaum: Stony Brook University, Departments of Computer Science and Applied Mathematics & Statistics

DOI: https://doi.org/10.1038/s41598-017-07551-8
Journal volume & issue: Vol. 7, no. 1
pp. 1 – 9

Abstract

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Abstract In this note, we combined pediatric sarcoma data from Columbia University with adult sarcoma data collected from TCGA, in order to see if one can automatically discern a unique pediatric cluster in the combined data set. Using a novel clustering pipeline based on optimal transport theory, this turned out to be the case. The overall methodology may find uses for the classification of data from other biological networking problems.

Published in Scientific Reports

ISSN: 2045-2322 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Medicine; Science
Website: https://www.nature.com/srep/

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