A "Long Indel" model for evolutionary sequence alignment

We present a new probabilistic model of sequence evolution, allowing indels of arbitrary length, and give sequence alignment algorithms for our model. Previously implemented evolutionary models have allowed (at most) single-residue indels or have introduced artifacts such as the existence of indivisible "fragments." We compare our algorithm to these previous methods by applying it to the structural homology dataset HOMSTRAD, evaluating the accuracy of (1) alignments and (2) evolutionary time estimates. With our method, it is possible (for the first time) to integrate probabilistic sequence alignment, with reliability indicators and arbitrary gap penalties, in the same framework as phylogenetic reconstruction. Our alignment algorithm requires that we evaluate the likelihood of any specific path of mutation events in a continuous-time Markov model, with the event times integrated out. To this effect, we introduce a "trajectory likelihood" algorithm (Appendix A). We anticipate that this algorithm will be useful in more general contexts, such as Markov Chain Monte Carlo simulations.     

Extensive mtDNA variation within the yellow-pine chipmunk,Tamias amoenus (Rodentia: Sciuridae), and phylogeographic inferences for northwest North America

The yellow-pine chipmunk, Tamias amoenus, is common in xerophytic forests throughout much of northwest North America. We analyzed cytochrome b sequence variation from 155 individuals representing 57 localities across the distribution of T. amoenus including 10 additional species of Tamias. Maximum likelihood and parsimony tree estimation methods were used in conjunction with nested clade analysis to infer both deep and population-level processes. Our results indicate that two currently recognized subspecies of T. amoenus (T. a. canicaudus and T. a. cratericus) are not nested within other samples of T. amoenus. Maximum uncorrected levels of intraspecific sequence divergence within remaining samples of T. amoenus are >7%. Substantial geographic variation is characterized by 12 well-supported clades that correspond to distinct mountain ranges, but do not necessarily follow existing subspecific taxonomy. Significant association between geography and genealogy was detected within many of these clades and can be attributed to different population-level processes including past fragmentation, recent range expansion, and isolation by distance.     

A semiparametric empirical likelihood method for data from an outcome-dependent sampling scheme with a continuous outcome

Outcome-dependent sampling (ODS) schemes can be a cost effective way to enhance study efficiency. The case-control design has been widely used in epidemiologic studies. However, when the outcome is measured on a continuous scale, dichotomizing the outcome could lead to a loss of efficiency. Recent epidemiologic studies have used ODS sampling schemes where, in addition to an overall random sample, there are also a number of supplemental samples that are collected based on a continuous outcome variable. We consider a semiparametric empirical likelihood inference procedure in which the underlying distribution of covariates is treated as a nuisance parameter and is left unspecified. The proposed estimator has asymptotic normality properties. The likelihood ratio statistic using the semiparametric empirical likelihood function has Wilks-type properties in that, under the null, it follows a chi-square distribution asymptotically and is independent of the nuisance parameters. Our simulation results indicate that, for data obtained using an ODS design, the semiparametric empirical likelihood estimator is more efficient than conditional likelihood and probability weighted pseudolikelihood estimators and that ODS designs (along with the proposed estimator) can produce more efficient estimates than simple random sample designs of the same size. We apply the proposed method to analyze a data set from the Collaborative Perinatal Project (CPP), an ongoing environmental epidemiologic study, to assess the relationship between maternal polychlorinated biphenyl (PCB) level and children's IQ test performance.     

The finite polygenic mixed model: An alternative formulation for the mixed model of inheritance

This paper presents a mixed model of inheritance with a finite number of polygenic loci. This model leads to a likelihood that can be calculated using efficient algorithms developed for oligogenic models. For comparison, likelihood profiles were obtained for the finite polygenic mixed model, the usual mixed model, with exact and approximate calculations, and for a class D regressive model. The profiles for the finite polygenic mixed model were closest to the profiles for the usual mixed model with exact calculations.