Mapping temporally varying quantitative trait loci in time to failure experiments
Abstract (Summary)
Existing methods for mapping quantitative trait loci (QTL) in time-to-failure
experiments assume that the QTL effect is constant over the course of the study. This
assumption may be violated when the gene(s) underlying the QTL are up- or downregulated
on a biologically meaningful time-scale. In such situations, models that
assume a constant effect can fail to detect QTL in a whole genome scan. To
investigate this possibility, we utilize an extension of the Cox model (EC-model)
within an interval-mapping framework. In its simplest form, this model assumes that
the QTL effect changes at some time point t0, and follows a linear function before and
after this change point. The approximate time point at which this change occurs is
estimated. Using simulated and real data, we explore the mapping performance of the
EC-model to the Cox Proportional Hazards model (CPH-model), which explicitly
assumes a constant effect. The results show that the EC- model detects timedependent
QTL, which the CPH model fails to detect. At the same time, the ECmodel
recovers all of the QTL the CPH-model detects. We conclude that potentially
important QTL may be missed if their time-dependent effects are not accounted for.
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Bibliographical Information:
Advisor:
School:Pennsylvania State University
School Location:USA - Pennsylvania
Source Type:Master's Thesis
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