Past Pilot Awardee Granted $2M to Develop Better Statistics to Measure MicroRNA
Matthew McCall, Ph.D., associate professor of Biostatistics at URMC, was recently awarded his first R01 grant from the National Institute of General Medical Sciences to develop statistical methods to improve the analysis of microRNA-sequencing data. Application of these methods will help uncover how alterations in microRNA abundance contribute to human disease.
McCall’s research has focused on building statistical methods to better understand microRNA, which regulate gene expression and contribute to a variety of human diseases if they malfunction. In an effort to build a microRNAome, McCall developed statistical methods to better estimate where microRNAs are expressed in human cells and tissues, made possible by McCall’s previous UR CTSI-supported pilot funding.
In the course of his UR CTSI Novel Biostatistical and Epidemiological Methods Pilot project, McCall quickly realized that methods developed to analyze mRNA sequencing data would not work for microRNA data. There are several assumptions that statistical methods make for mRNA sequencing data that do not hold true for microRNA.
“Despite their importance, our understanding of the role of microRNAs is hampered by a lack of statistical methods designed specifically to analyze microRNA-sequencing data,” said McCall.
With his new grant, McCall aims to do just that: develop statistical methods that directly address the challenges unique to measuring expression levels of microRNAs. Those challenges include a lack of independence between microRNA counts, significant variation in the overall transcription level across samples, and imbalance of over- and under-expressed features when comparing any two samples.
By addressing these challenges and improving the analysis of microRNA-sequencing data, McCall hopes his project will help identify how changes in microRNA abundance contribute to many human disease processes, including heart disease and cancer. And he plans to continue that work alongside his long-term collaborator, Marc K. Halushka, M.D., Ph.D., professor of pathology and oncology at Johns Hopkins School of Medicine
The project described in this article was supported by a UR CTSI Novel Biostatistical and Epidemiological Methods Pilot Award through the University of Rochester CTSA award number UL1 TR002001 from the National Center for Advancing Translational Sciences of the National Institutes of Health. The UR CTSI NBEM Pilot awards support the development of novel biostatistical and epidemiologic methods that overcome analytic limitations and enhance the validity, accuracy, scope or speed of clinical or translational research.
If you would like to share a similar success story that you attribute to UR CTSI support, please email Susanne_Pallo@urmc.rochester.edu.
Susanne Pritchard Pallo |