Ontology highlight
ABSTRACT:
SUBMITTER: Huang H
PROVIDER: S-EPMC4706235 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America 20151210 4
Clustering methods have led to a number of important discoveries in bioinformatics and beyond. A major challenge in their use is determining which clusters represent important underlying structure, as opposed to spurious sampling artifacts. This challenge is especially serious, and very few methods are available, when the data are very high in dimension. Statistical Significance of Clustering (SigClust) is a recently developed cluster evaluation tool for high dimensional low sample size data. An ...[more]