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1. Pediatric Sarcoma Data Forms a Unique Cluster Measured via the Earth Mover's Distance.

Author

Chen Y, Cruz FD, Sandhu R, Kung AL, Mundi P, Deasy JO, and Tannenbaum A

Subjects
Age Factors, Colombia, Humans, Biostatistics methods, Cluster Analysis, Gene Expression Profiling, Pattern Recognition, Automated methods, Sarcoma pathology
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
2017
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