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Activity Number: 360 - New Areas in Complex High-Dimensional Data Analysis
Type: Invited
Date/Time: Wednesday, August 10, 2022 : 8:30 AM to 10:20 AM
Sponsor: International Indian Statistical Association
Abstract #320609
Title: Phylogenetically Informed Methods for Microbiome Data Analysis
Author(s): Julia Fukuyama*
Companies: Indiana University, Bloomington
Keywords: pca; mds; phylogeny; eigendecomposition
Abstract:

Abstract: Phylogenetically-informed distances are widely used in ecology, often in conjunction with multi-dimensional scaling, to describe the relationships between communities of organisms and the taxa they comprise. A large number of such distances have been developed, each leading to a different representation of the communities. The ecology literature often tries to interpret the differences between representations given by different distances, but without a good understanding of the properties of the distances it is unclear how useful these interpretations are. I give an overview of some of these distances, describe the interpretational challenges they pose, develop some interesting properties, and comment on opportunities for improvement.


Authors who are presenting talks have a * after their name.

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