Browsing by Subject "mixed models"
Now showing 1 - 6 of 6
- Results Per Page
- Sort Options
Item Evolution of Rhizaria: New insights From Phylogenomic Analysis of Uncultivated Protists(2010-12) Burki, Fabien; Kudryavtsev, Alexander; Matz, Mikhail V.; Aglyamova, Galina V.; Bulman, Simon; Fiers, Mark; Keeling, Patrick J.; Pawlowski, Jan; Matz, Mikhail V.; Aglyamova, Galina V.Recent phylogenomic analyses have revolutionized our view of eukaryote evolution by revealing unexpected relationships between and within the eukaryotic supergroups. However, for several groups of uncultivable protists, only the ribosomal RNA genes and a handful of proteins are available, often leading to unresolved evolutionary relationships. A striking example concerns the supergroup Rhizaria, which comprises several groups of uncultivable free-living protists such as radiolarians, foraminiferans and gromiids, as well as the parasitic plasmodiophorids and haplosporids. Thus far, the relationships within this supergroup have been inferred almost exclusively from rRNA, actin, and polyubiquitin genes, and remain poorly resolved. To address this, we have generated large Expressed Sequence Tag (EST) datasets for 5 species of Rhizaria belonging to 3 important groups: Acantharea (Astrolonche sp., Phyllostaurus sp.), Phytomyxea (Spongospora subterranea, Plasmodiophora brassicae) and Gromiida (Gromia sphaerica). Results: 167 genes were selected for phylogenetic analyses based on the representation of at least one rhizarian species for each gene. Concatenation of these genes produced a supermatrix composed of 36,735 amino acid positions, including 10 rhizarians, 9 stramenopiles, and 9 alveolates. Phylogenomic analyses of this large dataset revealed a strongly supported clade grouping Foraminifera and Acantharea. The position of this clade within Rhizaria was sensitive to the method employed and the taxon sampling: Maximum Likelihood (ML) and Bayesian analyses using empirical model of evolution favoured an early divergence, whereas the CAT model and ML analyses with fast-evolving sites or the foraminiferan species Reticulomyxa filosa removed suggested a derived position, closely related to Gromia and Phytomyxea. In contrast to what has been previously reported, our analyses also uncovered the presence of the rhizarian-specific polyubiquitin insertion in Acantharea. Finally, this work reveals another possible rhizarian signature in the 60S ribosomal protein L10a. Conclusions: Our study provides new insights into the evolution of Rhizaria based on phylogenomic analyses of ESTs from three groups of previously under-sampled protists. It was enabled through the application of a recently developed method of transcriptome analysis, requiring very small amount of starting material. Our study illustrates the potential of this method to elucidate the early evolution of eukaryotes by providing large amount of data for uncultivable free-living and parasitic protists.Item Fast and Accurate Methods for Phylogenomic Analyses(2011-10) Yang, Jimmy; Warnow, Tandy; Yang, Jimmy; Warnow, TandySpecies phylogenies are not estimated directly, but rather through phylogenetic analyses of different gene datasets. However, true gene trees can differ from the true species tree (and hence from one another) due to biological processes such as horizontal gene transfer, incomplete lineage sorting, and gene duplication and loss, so that no single gene tree is a reliable estimate of the species tree. Several methods have been developed to estimate species trees from estimated gene trees, differing according to the specific algorithmic technique used and the biological model used to explain differences between species and gene trees. Relatively little is known about the relative performance of these methods. Results: We report on a study evaluating several different methods for estimating species trees from sequence datasets, simulating sequence evolution under a complex model including indels (insertions and deletions), substitutions, and incomplete lineage sorting. The most important finding of our study is that some fast and simple methods are nearly as accurate as the most accurate methods, which employ sophisticated statistical methods and are computationally quite intensive. We also observe that methods that explicitly consider errors in the estimated gene trees produce more accurate trees than methods that assume the estimated gene trees are correct. Conclusions: Our study shows that highly accurate estimations of species trees are achievable, even when gene trees differ from each other and from the species tree, and that these estimations can be obtained using fairly simple and computationally tractable methods.Item A Joint Model for the Perfect and Imperfect Substitute Goods Case: Application to Activity Time-Use Decisions(Elsevier, 2006) Bhat, Chandra R.; Srinivasan, Sivaramakrishnan; Sen, SudeshnaThis paper formulates a model for the joint analysis of the imperfect and perfect substitute goods case. That is, it enables the modeling of choice situations where consumers choose multiple alternatives at the same time from a certain set of alternatives, but also choose only one alternative from among a subset of alternatives. For example, in the context of time-use in leisure activity, individuals may participate in combinations of social, out-of-home recreation, and out-of-home non-maintenance shopping pursuits. These three activity types are imperfect substitutes in that they serve different functional needs of individuals and households. However, if an individual participates in out-of-home recreation, s/he may participate in only one of physically passive activities (for example, going to the movies), partially physically active activities (going to the beach or participating in spectator sports), or physically active activities (for example, working out at a gym) during a given time period (such as a weekday or a weekend day). To our knowledge, this paper is the first to consider a unified utility-maximizing framework for the analysis of such a joint imperfect-perfect substitute goods case in the economic literature. The model formulated in the paper is applied to the time-use decisions of individuals. Specifically, individual time-use in maintenance and leisure activities are modeled as a function of demographic variables, urban environment attributes, and day of week/season effects. The results from the model can be used to examine time use choices across different segments of the population (for example, male vs. female, young vs. old, etc.), as well as to assess the potential impact of urban form policies on individual time use decisions.Item The MACML Estimation of the Normally-Mixed Multinomial Logit Model(2011-01-18) Bhat, Chandra R.The focus of this paper is to develop a procedure for the Maximum Composite Marginal Likelihood (MACML) estimation of multinomial logit models with normally mixed terms, as would be the case with normally-mixed random coefficient and/or error-component structures.Item The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models(Elsevier, 2011) Bhat, Chandra R.The likelihood functions of multinomial probit (MNP)-based choice models entail the evaluation of analytically-intractable integrals. As a result, such models are usually estimated using maximum simulated likelihood (MSL) techniques. Unfortunately, for many practical situations, the computational cost to ensure good asymptotic MSL estimator properties can be prohibitive and practically infeasible as the number of dimensions of integration rises. In this paper, we introduce a maximum approximate composite marginal likelihood (MACML) estimation approach for MNP models that can be applied using simple optimization software for likelihood estimation. It also represents a conceptually and pedagogically simpler procedure relative to simulation techniques, and has the advantage of substantial computational time efficiency relative to the MSL approach. The paper provide s a “blueprint” for the MACML estimation for a wide variety of MNP models.Item A New Approach to Specify and Estimate Non-Normally Mixed Multinomial Probit Models(Elsevier, 2012) Bhat, Chandra R.; Sidharthan, RaghuprasadThe current paper proposes the use of the multivariate skew-normal distribution function to accommodate non-normal mixing in cross-sectional and panel multinomial probit (MNP) models. The combination of skew-normal mixing and the MNP kernel lends itself nicely to estimation using Bhat’s (2011) maximum approximate composite marginal likelihood (MACML) approach. Simulation results for the cross-sectional case show that our proposed approach does well in recovering the underlying parameters, and also highlights the pitfalls of ignoring non-normality of the continuous mixing distribution when such non-normality is present. At the same time, the proposed model obviates the need to assume a pre-specified parametric distribution for the mixing, and allows the estimation of a very flexible, but still parsimonious, mixing distribution form.