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PubMed2005

A Bayesian approach for discriminating among alternative inheritance hypotheses in plant polyploids: the allotetraploid origin of genus Borderea (Dioscoreaceae).

Polyploidy is a common phenomenon occurring in a vast number of land plants. Investigations of patterns of inheritance and the origins of plants (i.e., autopolyploidy vs. allopolyploidy) usually involve cytogenetic and molecular studies of chromosome pairing, chromosome mapping, and marker segregation analysis through experimental crosses and progeny tests. Such studies are missing for most wild species, for which artificial crosses are difficult, not feasible, or unaffordable. We report here a Bayesian method to discriminate between alternative inheritance patterns in the two extant, tetraploid species of the monocot genus Borderea (Dioscoreaceae), which does not involve progeny array tests. Our approach is based on the screening of a large number of SSR genotypes, which were obtained from successful amplifications of 17 microsatellite regions in individuals of both B. chouardii and B. pyrenaica. We tested for tetrasomic vs. disomic modes of inheritance, using the Bayes factor test. Assignment of genotypes under both alternatives could be unequivocally done for 14 and 11 of the 17 studied microsatellite regions in B. chouardii and B. pyrenaica, respectively, totaling 9502 analyzed genotypes. The comparison of posterior probabilities for the two competing hypotheses across the surveyed loci clearly favored a disomic inheritance pattern. Linkage tests indicated that none of the studied SSR loci were in linkage disequilibrium, thus representing independent samples of the Borderea genome. These results, along with previous allozyme data, support the allotetraploid origin of this paleoendemic genus and reveal the lowest reported chromosome base number for the family of the yams.

Bayes Theorem↗
PubMed2005

Bayesian analysis of quantitative trait loci for boar taint in a Landrace outbred population.

The genetic basis of the main components of boar taint was investigated in intact male pigs in a commercial population. We analyzed fat androsten-one and skatole concentrations from 217 males of an outbred Landrace population. Records were normalized using a logarithm transformation and tested for normality using a Wilk-Shapiro test. Bayesian analysis was then used to map QTL in 10 candidate regions previously selected on chromosomes 1, 2, 3, 4, 6, 7, 8, 9, 10, and 13. The criterion for QTL detection was the Bayes factor (BF) between polygenic models with and without QTL effects. Both traits had considerable genetic determination, with posterior means of total heritabilities ranging from 0.59 to 0.73 for androstenone and from 0.74 to 0.89 for skatole. Positive evidence for a fat skatole QTL was detected on SSC6 (BF = 5.16); however, no QTL for androstenone were found in any of the 10 chromosomal regions analyzed. With the detection of a QTL for the fat skatole concentration segregating in this population, marker-assisted selection or even gene-assisted selection could be used once the causal mutation of the QTL was identified.

Adipose Tissue↗
PubMed2005

Cerebral pathways in processing of affective prosody: a dynamic causal modeling study.

This study was conducted to investigate the connectivity architecture of neural structures involved in processing of emotional speech melody (prosody). 24 subjects underwent event-related functional magnetic resonance imaging (fMRI) while rating the emotional valence of either prosody or semantics of binaurally presented adjectives. Conventional analysis of fMRI data revealed activation within the right posterior middle temporal gyrus and bilateral inferior frontal cortex during evaluation of affective prosody and left temporal pole, orbitofrontal, and medial superior frontal cortex during judgment of affective semantics. Dynamic causal modeling (DCM) in combination with Bayes factors was used to compare competing neurophysiological models with different intrinsic connectivity structures and input regions within the network of brain regions underlying comprehension of affective prosody. Comparison on group level revealed superiority of a model in which the right temporal cortex serves as input region as compared to models in which one of the frontal areas is assumed to receive external inputs. Moreover, models with parallel information conductance from the right temporal cortex were superior to models in which the two frontal lobes accomplish serial processing steps. In conclusion, connectivity analysis supports the view that evaluation of affective prosody requires prior analysis of acoustic features within the temporal and that transfer of information from the temporal cortex to the frontal lobes occurs via parallel pathways.

Adult↗
PubMedDate not supplied

A multiple imputation strategy for incomplete longitudinal data.

Longitudinal studies are commonly used to study processes of change. Because data are collected over time, missing data are pervasive in longitudinal studies, and complete ascertainment of all variables is rare. In this paper a new imputation strategy for completing longitudinal data sets is proposed. The proposed methodology makes use of shrinkage estimators for pooling information across geographic entities, and of model averaging for pooling predictions across different statistical models. Bayes factors are used to compute weights (probabilities) for a set of models considered to be reasonable for at least some of the units for which imputations must be produced, imputations are produced by draws from the predictive distributions of the missing data, and multiple imputations are used to better reflect selected sources of uncertainty in the imputation process. The imputation strategy is developed within the context of an application to completing incomplete longitudinal variables in the so-called Area Resource File. The proposed procedure is compared with several other imputation procedures in terms of inferences derived with the imputations, and the proposed methodology is demonstrated to provide valid estimates of model parameters when the completed data are analysed. Extensions to other missing data problems in longitudinal studies are straightforward so long as the missing data mechanism can be assumed to be ignorable.

Bayes Theorem↗
PubMed2003

Assessment of homogeneity vs. heterogeneity of residual variance in random regression test-day models in a Bayesian analysis.

Test-day first-lactation milk yields from Holstein cows were analyzed with a set of random regression models based on Legendre polynomials of varying order on additive genetic and permanent environmental effects. Homogeneity and heterogeneity of residual variance, assuming three and 30 arbitrary measurement error classes of different length were considered. Unknown parameters were estimated within a Bayesian framework. Bayes factors and a checking function for the cross-validation predictive densities of the data were the tools chosen for selecting among competing models. Residual variances obtained from 30 arbitrary intervals were nearly constant between d 70 and 300 and tended to increase towards the extremes of the lactation, especially at the onset. In early lactation, the temporary measurement errors were found to be larger and highly variable. A high order of the regression submodels employed for modeling the permanent environmental deviations tended to strongly correct the heterogeneity of the residual variance. Accordingly, the assumption of homogeneity of residual variance was the most plausible specification under both comparison criteria when the number of random regression coefficients was set to five. Otherwise, the heterogeneity assumption, using three or 30 error classes, was better supported, depending on the criterion and on the order of the submodel fitted for the permanent environmental effect.

Analysis of Variance↗
PubMed2001

Bayesian selection of continuous-time Markov chain evolutionary models.

We develop a reversible jump Markov chain Monte Carlo approach to estimating the posterior distribution of phylogenies based on aligned DNA/RNA sequences under several hierarchical evolutionary models. Using a proper, yet nontruncated and uninformative prior, we demonstrate the advantages of the Bayesian approach to hypothesis testing and estimation in phylogenetics by comparing different models for the infinitesimal rates of change among nucleotides, for the number of rate classes, and for the relationships among branch lengths. We compare the relative probabilities of these models and the appropriateness of a molecular clock using Bayes factors. Our most general model, first proposed by Tamura and Nei, parameterizes the infinitesimal change probabilities among nucleotides (A, G, C, T/U) into six parameters, consisting of three parameters for the nucleotide stationary distribution, two rate parameters for nucleotide transitions, and another parameter for nucleotide transversions. Nested models include the Hasegawa, Kishino, and Yano model with equal transition rates and the Kimura model with a uniform stationary distribution and equal transition rates. To illustrate our methods, we examine simulated data, 16S rRNA sequences from 15 contemporary eubacteria, halobacteria, eocytes, and eukaryotes, 9 primates, and the entire HIV genome of 11 isolates. We find that the Kimura model is too restrictive, that the Hasegawa, Kishino, and Yano model can be rejected for some data sets, that there is evidence for more than one rate class and a molecular clock among similar taxa, and that a molecular clock can be rejected for more distantly related taxa.

Animals↗
PubMed2005

Two ATM variants and breast cancer risk.

The ATM gene is mutated in ataxia-telangiectasia (AT). Heterozygote female relatives of AT cases have a 2-7fold increased risk of breast cancer. We previously reported high risks of breast cancer associated with certain ATM variants. To estimate the risks more precisely, we have examined two ATM variants, c.1066-6T>G (IVS10-6T>G) and c.4258C>T (p.Leu1420Phe), in additional cases and controls from the same Australian cohorts previously used to estimate the risk of breast cancer associated with c.1066-6T>G. A total of 775 and 84 population-based controls were genotyped for the c.1066-6T>G and c.4258C>T ATM variants respectively, as were index cases from 378 and 373 non-BRCA1/2 breast cancer families. Penetrance was estimated by Bayes factor analysis. The allele frequencies of ATM c.1066-6T>G and c.4258C>T estimated from controls were 0.005 (95% CI=0.002 to 0.009) and 0.012 (95% CI=0.001 to 0.042), respectively. We identified three new breast cancer families with c.1066-6T>G, and seven families with c.4258C>T. Combining with the two c.1066-6T>G families previously reported, the estimated penetrance to age 70 of c.1066-6T>G was 17.2% (95% CI=4.7% to 37.5%). For c.4258C>T, the estimated average penetrance was 4.8% (95% CI 1.7% to 10.1%). In conclusion, we found no evidence that the ATM c.4258C>T variant increases breast cancer risk, and little evidence that c.1066-6T>G confers an elevated risk. Analysis of additional families will be necessary to define more precisely the risk, if any, associated with c.1066-6T>G.

Ataxia Telangiectasia Mutated Proteins↗
PubMed2004

Hierarchical Bayes multiple-breed inference with an application to genetic evaluation of a Nelore-Hereford population.

The primary objective of this study was to demonstrate the utility of a hierarchical Bayes implementation of a multiple-breed animal model (MBAM) to estimate breed composition means and additive genetic variances as well as on variances due to the segregation between breeds. The MBAM and a conventional animal model (AM) were both applied to five simulated data sets derived from each of two different populations. Population I consisted of crosses between two breeds having a twofold difference in genetic variance and a nonzero segregation variance. Population II had the same population structure as Population I, except that the two breeds had the same genetic variance with no segregation variance; that is, Population II was essentially single breed in its genetic architecture. For Population I, posterior means of all variance components obtained by MBAM were unbiased, with 95% posterior probability intervals (PPI) having the expected coverage based on five replicates. The MBAM showed a slightly superior performance over the AM for genetic predictions in Population I, although there was no evidence that the use of the MBAM translated into greater genetic gains relative to the use of the AM. Nevertheless, the MBAM was clearly demonstrated to have superior fit to the data using pseudo-Bayes factors (PBF) as the basis for model choice. As expected, the MBAM and AM performed equally well in Population II. A data set consisting of 22,717 postweaning gain (PWG) records of a Nelore-Hereford population (40,082 animals in the pedigree) also was analyzed. The MBAM inference on Nelore and Hereford additive heritabilities (h2A) substantially differed. Herefords had a posterior mean h2A of 0.20 with a 95% PPI of 0.15 to 0.25, whereas the corresponding values for the Nelores were 0.07 and 0.04 to 0.11, respectively. The posterior mean genetic variance due to the segregation between these breeds was 8.4 kg2, with a 95% PPI of 2.3 to 24.8 kg2, and represented 35.4% of the Nelore but only 9.9% of the Hereford posterior mean genetic variance. The posterior mean h2A using the AM was 0.15, presumed common across the two breeds, with a 95% PPI of 0.11 to 0.19. The PBF heavily favored the MBAM over the AM for the PWG data. Accordingly, the MBAM represents a viable alternative to AM for multiple-breed genetic evaluations, providing the necessary flexibility in modeling heteroskedastic genetic variances of breed composition groups.

Algorithms↗
PubMed2003

A method for evaluating the results of Bayesian model selection: application to linkage analyses of attributes determined by two or more genes.

OBJECTIVES: We apply and evaluate the intrinsic Bayes factor (IBF) of Berger and Pericchi [J Am Stat Assoc 1996;91:109-122; Bayesian Statistics, Oxford University Press, vol 5, 1996] to linkage analyses done using the stochastic search variable selection (SSVS) method of George and McCulloch [J Am Stat Assoc 1993;88:881-889] as proposed by Suh et al. [Genet Epidemiol 2001;21(suppl 1):S706-S711]. METHODS: We consider 20 simulations of linkage data obtained under two different generating models. The SSVS is applied to a multiple regression extension [Genet Epidemiol 2001;21(suppl 1): S706-S711] of the Haseman-Elston [Behav Genet 1972;2:3-19; Genet Epidemiol 2000;19:1-17] methods. Four prior distributions are considered. We apply the IBF criterion to those samples where different prior distributions result in different top models. RESULTS: In those samples where three different models were obtained using the four priors, application of the IBFs eliminated one of the two wrong models in 4 out of 5 situations. Further elimination using the IBF criterion for situations with two different subsets did not serve as well. CONCLUSIONS: When different priors result in three or more different subsets of markers, one can use the IBF to get this number down to two for consideration. When two subsets result we recommend that both be considered.

Bayes Theorem↗
PubMed2003

Bayesian estimates of covariance components between lactation curve parameters and disease liability in Danish Holstein cows.

In the present work, covariance components for milk yield and disease liability were estimated with bivariate random regression test-day sire models using a Bayesian approach and implemented via the Gibbs sampler. The data consist of 8075 first-parity Danish Holstein (DH) cows, from 1259 sires, performing in 57 herds from 1992 to 1997. Treatments associated with five different type of diseases were pooled into a single general disease liability for each cow. Two models were fitted to the data. First, using a bivariate model, milk yield is modeled via a random regression, and disease liability via a repeatablility model. Second, using a bivariate model, both milk yield and disease liability are modeled using random regressions. A comparison based on a Bayes factor provides very strong support for the bivariate random regression model. Posterior means of heritabilities for each of the traits were estimated for five different points in time throughout lactation. Across models, heritabilities for milk yield are lowest in the beginning of the lactation (0.19) and highest at the end of the lactation (0.35). Posterior means of heritabilities of disease liability range from 0.04 to 0.10 for test days, and is equal to 0.20 for the whole lactation. Heritability of persistency measures estimated from the two models are 0.20 and 0.21. Estimates of posterior means of genetic correlations between single test-day milk yield and single test-day disease liability are in the range of 0.31 to 0.57. The estimates of posterior mean and of the 95% posterior interval of the genetic correlation between persistency and (total) disease liability using the model with the highest posterior probability are -0.12 and (-0.44; 0.20), respectively. Even though the largest proportion of the posterior probability mass is spread along negative values of the correlation (indicating that individuals with a flatter lactation curve tend to have lower disease liability), a value of zero of the genetic correlation falls comfortably within the 95% posterior interval. Thus the prospects of reducing incidence of disease by manipulating persistency as defined in this work remain inconclusive.

Animals↗
PubMed2006

Accounting for variation of substitution rates through time in Bayesian phylogeny reconstruction of Sapotoideae (Sapotaceae).

We used Bayesian phylogenetic analysis of 5 kb of chloroplast DNA data from 68 Sapotaceae species to clarify phylogenetic relationships within Sapotoideae, one of the two major clades within Sapotaceae. Variation in substitution rates through time was shown to be a very important aspect of molecular evolution for this data set. Relative rates tests indicated that changes in overall rate have taken place in several lineages during the history of the group and Bayes factors strongly supported a covarion model, which allows the rate of a site to vary over time, over commonly used models that only allow rates to vary across sites. Rate variation over time was actually found to be a more important model component than rate variation across sites. The covarion model was originally developed for coding gene sequences and has so far only been tested for this type of data. The fact that it performed so well with the present data set, consisting mainly of data from noncoding spacer regions, suggests that it deserves a wider consideration in model based phylogenetic inference. Repeatability of phylogenetic results was very difficult to obtain with the more parameter rich models, and analyses with identical settings often supported different topologies. Overparameterization may be the reason why the MCMC did not sample from the posterior distribution in these cases. The problem could, however, be overcome by using less parameter rich evolutionary models, and adjusting the MCMC settings. The phylogenetic results showed that two taxa, previously thought to belong in Sapotoideae, are not part of this group. Eberhardtia aurata is the sister of the two major Sapotaceae clades, Chrysophylloideae and Sapotoideae, and Neohemsleya usambarensis belongs in Chrysophylloideae. Within Sapotoideae two clades, Sideroxyleae and Sapoteae, were strongly supported. Bayesian analysis of the character history of some floral morphological traits showed that the ancestral type of flower in Sapotoideae may have been characterized by floral parts (sepals, petals, stamens, and staminodes) in single whorls of five, entire corolla lobes, and seeds with an adaxial hilum.

Bayes Theorem↗
PubMed1996

Applications of a mixture survival model with covariates to the analysis of a depression prevention trial.

This paper presents a case study of model selection for survival analysis data. We use an approximate Bayesian method for model selection based on assessing the posterior probability of competing models given the data. We introduce the Schwarz criteria, an approximation to the logarithm of the Bayes factor, to provide an indication of evidence in favour of one model compared to another. Specifically, in the context of a depression prevention clinical trial we evaluate the efficacy of treatment in preventing or delaying the time to recurrence of depression, and evaluate how differences in the survival distributions between the two treatment groups depend on explanatory variables of interest. This investigation is based on a mixture survival model that explicitly incorporates the possibility of a surviving fraction.

Antidepressive Agents, Tricyclic↗
PubMed2026

Modulating sentence comprehension in people with aphasia through anodal tDCS: A double-blind randomized cross-over study.

This double-blind randomized cross-over study investigated the effects of perilesional anodal transcranial direct current stimulation (AtDCS) combined with speech-language therapy on sentence comprehension in eight individuals with chronic nonfluent agrammatic aphasia. The behavioral therapy consisted of an intensive comprehension treatment including drilling in sentence-to-picture matching and Mapping Therapy. Each participant underwent both the anodal tDCS and sham stimulation conditions (five received sham first followed by real stimulation, and the remaining three the reverse sequence), with each condition paired with the same behavioral treatment and separated by a four-month washout period. Stimulation was applied over the perilesional area (left BA6) for 20 min during daily 40-min therapy sessions over four consecutive weeks. Sentence comprehension was assessed with the RiComprendo battery and functional communication with the Communicative Effectiveness Index (CETI). Data were analyzed using paired t-tests, Bayesian analyses, and linear mixed-effects models to control for baseline performance and individual variability. Both stimulation conditions produced significant pre-to-post improvements in sentence comprehension, particularly for syntactically complex structures such as passives and center-embedded object relatives. However, gains were overall greater following AtDCS, as reflected in larger effect sizes, stronger Bayes factors, and a significant treatment effect in the mixed-effects models. Only the AtDCS condition yielded significant improvements in self-perceived comprehension abilities on the CETI. These findings suggest that AtDCS over perilesional cortical areas may boost the effects of traditional language therapy on sentence comprehension, supporting its feasibility and potential as an adjuvant intervention in post-stroke aphasia rehabilitation.

Humans↗
PubMed2003

Normal linear models with genetically structured residual variance heterogeneity: a case study.

Normal mixed models with different levels of heterogeneity in the residual variance are fitted to pig litter size data. Exploratory analysis and model assessment is based on examination of various posterior predictive distributions. Comparisons based on Bayes factors and related criteria favour models with a genetically structured residual variance heterogeneity. There is, moreover, strong evidence of a negative correlation between the additive genetic values affecting litter size and those affecting residual variance. The models are also compared according to the purposes for which they might be used, such as prediction of 'future' data, inference about response to selection and ranking candidates for selection. A brief discussion is given of some implications for selection of the genetically structured residual variance model.

Analysis of Variance↗
PubMed2002

Sib-parentage testing using molecular markers when parents are unknown.

The formulae for computing the so-called Sib Index using codominant alleles for (1) full-sib and (2) half-sib parentage are given. Hypothesis testing is based on the distribution of conditional likelihood ratio or Bayes' factor. Thresholds for rejecting the null hypothesis and P-values were obtained in function of the number of alleles and their frequency distributions. Simulations showed that a relatively low number of marker systems (e.g. 20) are enough to accept the hypothesis of sib parentage with a reasonable power for usual significance levels, but that a higher number would be necessary if full-sib against half-sib parentage is the contrast to be carried out. The effect of sampling variation on the allele frequencies on power calculations is also analysed.

Alleles↗
PubMed1998

Missense mutations in disease genes: a Bayesian approach to evaluate causality.

The problem of interpreting missense mutations of disease-causing genes is an increasingly important one. Because these point mutations result in alteration of only a single amino acid of the protein product, it is often unclear whether this change alone is sufficient to cause disease. We propose a Bayesian approach that utilizes genetic information on affected relatives in families ascertained through known missense-mutation carriers. This method is useful in evaluating known disease genes for common disease phenotypes, such as breast cancer or colorectal cancer. The posterior probability that a missense mutation is disease causing is conditioned on the relationship of the relatives to the proband, the population frequency of the mutation, and the phenocopy rate of the disease. The approach is demonstrated in two cancer data sets: BRCA1 R841W and APC I1307K. In both examples, this method helps establish that these mutations are likely to be disease causing, with Bayes factors in favor of causality of 5.09 and 66.97, respectively, and posterior probabilities of .836 and .985. We also develop a simple approximation for rare alleles and consider the case of unknown penetrance and allele frequency.

Adenomatous Polyposis Coli↗
PubMed2007

Estimation of genetic parameters for cumulative egg numbers in a broiler dam line by using a random regression model.

The random regression model (RRM) methodology was applied to the estimation of genetic parameters for cumulative egg numbers and monthly egg production in a broiler dam line. The data were extracted from records of a commercial dam line in 2001 to 2003. A total of 99,193 records from 6,475 hens and 9,111 pedigreed animals were used in the current study. The variance components were estimated using Gibbs sampling procedure. According to the Bayesian information criterion and Bayes factor, an RRM with Legendre polynomial of 2 orders for hatching groups and additive genetic effects and of 4 orders for permanent environmental effects was chosen as the optimal model for cumulative egg numbers in the broiler dam line. The heritability estimates of the cumulative egg numbers between wk 1 and 40 of production ranged from 0.16 to 0.54, whereas heritability estimates from wk 12 to 20 of production were moderate. The ratios of permanent environmental variance to phenotypic variance were large, indicating that the RRM could produce better estimates of additive genetic effects. The genetic and phenotypic correlations between cumulative egg numbers at different production weeks estimated with the optimal RRM were generally higher when the overlapping weeks were greater. In addition, genetic parameters for monthly egg production could also be obtained by the optimal RRM, and the heritability estimates ranged from 0.03 to 0.18. It was suggested that early selection based on cumulative egg numbers in the first 19 wk of production could effectively improve annual egg production in the broiler dam line.

Animals↗
PubMed2025

Biallelic variants in RNU2-2 cause the most prevalent known recessive neurodevelopmental disorder.

We recently showed that mutations in RNU4-2 and RNU2-2, two genes that are transcribed into small nuclear RNA (snRNA) components of the major spliceosome, are prevalent causes of dominant neurodevelopmental disorders (NDDs). By genetic association comparing 12,776 NDD cases with 56,064 controls, we now demonstrate the existence of a recessive form of RNU2-2 syndrome that, in England, is even more common than the dominant form. We inferred log Bayes factors for dominant and recessive models of association of 14.0 and 18.2, respectively, and observed 17 rare variants with a posterior probability of pathogenicity conditional on recessive association >0.8. This conservative threshold identified 18 probands (all with unaffected parents) and five affected siblings, each carrying two alleles in trans at these variants. A relaxed threshold of >0.6 identified a further 13 candidate probands. We estimate that recessive RNU2-2 syndrome accounts for 7-10% of families with a diagnosed recessive NDD, and is 36-62% as prevalent as the dominant RNU4-2-related disorder ReNU syndrome. We identified a further seven cases in five pedigrees in two replication collections. Cases are characterized by intellectual disability, global developmental delay and seizures. The variants are predicted to destabilize stem loops and binding domains of the U2-2 snRNA that contribute to spliceosome quaternary structure, intron recognition and catalytic function. Despite this, whole-blood derived RNA-seq data from three patients did not reveal splicing defects, in line with previous analogous observations for dominant RNU2-2 syndrome.

Journal Article↗