Novel biostatistics methodology yields more efficient design and analysis of genomic studies
Co-authors are Danyu Lin, PhD, Dennis Gillings Distinguished Professor; Donglin Zeng, PhD, professor; and Zhengzheng Tang, doctoral student, all in the Gillings School’s Department of Biostatistics. Lin and Zeng are members of the UNC Lineberger Comprehensive Cancer Center.
Their research, “Quantitative trait analysis in sequencing studies under trait-dependent sampling,” was published online July 11 in the Proceedings of the National Academy of Sciences (PNAS).
When examining genetic traits in a large cohort, it is not economically feasible to sequence all cohort members. A cost-effective strategy is to select only the subjects who have extreme trait values. Not accounting for such “trait-dependent” sampling in the association analysis would substantially increase false-positive results and reduce true-positive results. Lin and colleagues developed valid and efficient methods for such analysis.
