Dr. Gail Rosen Published in PLOS ONE

Dr. Gail Rosen, Associate Professor in Electrical and Computer Engineering, and her Ph.D. advisee Zhengqiao Zhao have been published in the peer-reviewed, open access journal PLOS ONE.  The paper is entitled, “Exploring Thematic Structure and Predicted Functionality of 16S rRNA Amplicon Data.”

The abstract of the paper is below:

To understand the microbiome's role in health and the environment, researchers usually conduct a microbial census. Marker genes from microbial DNA are sampled from hosts and environmental sources.  It is difficult to determine which species (or other groups of taxa) from these surveys are associated with phenotypes of interest (e.g., disease states, soil fertility, etc.).  This difficulty is more compounded by the fact that species work together, and thus "co-occur".  A certain type of configuration of co-occurring taxa may be indicative of a phenotype.  For example these configurations can indicate: that one species may be highly abundant with others equally but lower in abundance, that there may be a dominant and co-dominant species, or any other type of configuration that one can think of.  Inferring subcommunitys' configurations as well as how these subcommunities co-exist under different environmental pressures needs advanced statistical models.  Also, no computational methods indicate how these subcommunities function metabolically.  We introduce a software package that researchers can use to explore subcommunities, their functions, and their relationships to phenotypes in a freely available R package. We demonstrate that we can discover subcommunities important to Inflammatory Bowel Disease, oral cancer, and show that the software can explore the way in which sets of co-occurring taxa behave and evolve over time.  This research advances one of NSF's 10 Big Idea's, specifically the Understanding the Rules of Life: Predicting Phenotype initiative.

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