Bioinformatics, Statistical Proteomics and Genomics and Systems Biology



Estimation of genetic effects on longitudinal and time-to-event livestock data

Project: Estimation of genetic effects on longitudinal and time-to-event livestock data


PI: Rodriguez-Zas, Sandra.

Grant Number: ILLU-538-350



The objectives are: 1. Develop and evaluate nonlinear mixed effects models that account for the between and within subject variation in the analysis of longitudinal data. 2. Study the relationship between longitudinal traits and time-to-event processes accounting for genetic and environmental sources of variation. 3. Examine the impact of censored records on the bias of the estimates on longitudinal and failure time analyses. 4. Generate statistical methods to detect QTL or major genes influencing discrete traits and the pattern of processes such as growth and production. A parametric sequential approach is proposed to develop statistical methods for agricultural longitudinal and failure time data. Parsimonious models and simple to implement classical and Bayesian methods will be developed. Application of this model to simulated data will help to identify the factors influencing gene detection. Analysis of simulated and real data will provide a better understanding of the advantages and limitations of the methodologies.


Rodriguez-Zas, S. L., Southey, B. R., Knox, R. V. and Connor, J. F. Study of factors influencing sow longevity in swine breeding herds. 2002. Journal of Animal Sciences 80, Suppl. 2, 45p.

Southey, B. R., Rodriguez-Zas, S. L., Knox, R.V., Connor, J. F. and Roskamp, B. 2002. Indirect long-term selection response of sow longevity. In: Proceedings of Long-Term Selection. A celebration of 100 generations of selection for oil and protein in maize. June 16-18, 2002. University of Illinois at Urbana-Champaign.

Southey B. R., Rodriguez-Zas S. L., Leymaster K. A. 2003. Discrete time survival analysis of lamb mortality in a terminal sire composite population. Journal of Animal Sciences 81(6):1399-1405.