Megan Orr, assistant professor of statistics, was invited to speak at the International Biometric Society Eastern North American Region 2014 Spring Meeting, held March 16-19, in Baltimore.
Orr’s talk, titled “Identifying genes that are differentially expressed in both of two independent experiments,” introduced a novel method for analyzing gene expression data across two experiments. The development of this method was motivated by methods described in an article with a similar title published in the December 2012 Journal of Agricultural, Biological and Environmental Statistics with Orr as the first author.
“Technologies for measuring gene expression are relatively new and constantly evolving. This leaves the door wide open for researchers to continually develop new and better methodologies for analyzing gene expression data,” Orr said. “Organisms, including humans, mice and corn, have tens of thousands of genes, and gene expression experiments generally have relatively small sample sizes, which makes identifying the truly important genes difficult. Simultaneously analyzing multiple experiments adds to this difficulty. However, if researchers are seeing a consistent set of significant genes across experiments, this allows them to see which genes have different expression levels across treatments, disease states or phenotypes.”
Orr plans to submit a manuscript of her current research for publication.
Orr joined NDSU in August 2012. She earned a Bachelor of Science in statistics from the University of Michigan and a doctorate in statistics from Iowa State University.
NDSU is recognized as one of the nation's top 108 public and private universities by the Carnegie Commission on Higher Education.