Pediatric Sarcoma Data Forms a Unique Cluster Measured via the Earth Mover's Distance. Academic Article uri icon

Overview

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.

publication date

  • August 1, 2017

Research

keywords

  • Biostatistics
  • Cluster Analysis
  • Gene Expression Profiling
  • Pattern Recognition, Automated
  • Sarcoma

Identity

PubMed Central ID

  • PMC5539155

Scopus Document Identifier

  • 85026744072

Digital Object Identifier (DOI)

  • 10.1038/s41598-017-07551-8

PubMed ID

  • 28765612

Additional Document Info

volume

  • 7

issue

  • 1