Faculty and Staff Directory
|Department:||Statistics, Biological Sciences
College of Arts and Sciences
|Office:||LeConte, Room 209G|
Ho Lab Website
Curriculum Vitae [pdf]
Department of Statistics
I enjoy working with data. I am currently working as an assistant professor at the Department of Statistics with a joint appointment in Biological Sciences at the University of South Carolina. I received a Ph.D. from the Department of Biostatistics at the Johns Hopkins University. My general research interests include computational biology, statistical genetics and statistical consulting. I am interested in developing statistical methods and algorithms for analyzing genetic data generated by high-throughput technologies, and gene pathway/network enrichment analysis. I also participate in collaborative research and provide statistical support for a wide range of exciting research topics such as genetic mechanisms for Hirschsprung disease, frailty in older women, and chemopreventive strategies for cancer.
1. Ho Y.-Y., Parmigiani, G., Louis, T.A., Cope, L.M. (2010). Modeling Liquid Association. Biometrics 67, 133-141. doi: 10.1111/j.1541-0420.2010.01440.x.
2. Ho Y.-Y., Matteini A.M., Beamer B., and Fried L., et al. (2011). Exploring biologically relevant pathways in frailty. Journal of Gerontology A Biological Sciences and Medical Sciences 66, 975-979.
3. Ho Y.-Y., Cope, L.M., Parmigiani, G. (2014). Modular network construction using eQTL data: an analysis of computational costs and benefits. Frontiers in Genetics 5, 40. doi: 10.3389/fgene.2014.00040
4. Ho Y.-Y., Baechler E.C., Ortmann W., Behrens T.W., Graham R.R., Bhangale T.R., Pan W. (2014). Using Gene Expression to Improve the Power of Genome-Wide Association Analysis. Human Heredity 78, 94-103. doi: 10.1159/000362837
5. Gunderson T.*, Ho Y.-Y.* (2014) An efficient algorithm to explore liquid association on a genome-wide scale. BMC Bioinformatics 15, 371.
6. Ho Y.-Y., O'Connell M., Guan W., Basu S. (2015) Powerful Association Test Combining Rare Variant and Gene Expression Using Family Data from Genetic Analysis Workshop 19. Genetic Analysis Workshop 19 Proceedings 9 Suppl 8, S33.
7. Ho Y.-Y., LaRue R.S., Timothy T. Starr, Largaespada D.A. (2016) Case-oriented pathways analysis in pancreatic adenocarcinoma using data from a sleeping beauty transposon mutagenesis screen. BMC Medical Genomics 9, 16.
8. Ho Y.-Y.*, Vo T.N.*, Chu H., LeSage M.G., Luo X., Le C.T. (2016) A Bayesian hierarchical model for demand curve analysis. *These authors contributed equally to this paper. Statistical Methods in Medical Research. DOI: 10.1177/0962280216673675
9. Abbott K, Ho Y.-Y., Erickson J. (2017) Automatic Health Record Review to Identify Gravely Ill Social Security Disability Applicants. Journal of the American Medical Informatics Association 24, 709-716.
10. Nallandhighal S., Park G.S., Ho Y.-Y., Opoka R. O., John C. C., Tran T.M. (2018) Blood transcriptional signatures related to erythropoietic and Nrf2 pathways dier between cerebral malaria and severe malarial anemia.
1. Ho Y.-Y., Cope L., Dettling M., and Parmigiani G. (2007). Statistical methods for identifying differentially expressed gene combinations. Methods in Molecular Biology 408, 171-191.
1. Ho, Y.-Y. (2009). LiquidAssociation: R/Bioconductor package for estimating liquid association using the conditional normal model. Available at http://www.bioconductor.org.
2. Gunderson T.* (2014). fastLiquidAssociation: R/Bioconductor package for exploring liquid association on a genome-wide scale. Available at http://www.bioconductor.org.