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PubMed2006

A Bayesian stopping rule for a single arm study: With a case study of stem cell transplantation.

Continuous monitoring of treatment failures is an important issue in clinical studies of a single experimental treatment for high risk therapy such as hematopoietic stem cell transplantation. The sequential probability ratio test (SPRT) of Wald in 1947 and various alternative stopping rules have been proposed for sequential monitoring of adverse events. It is natural to use prior information to improve stopping rules and statistical analysis. A Bayesian stopping rule is developed and applied to an example of an umbilical cord blood transplant study performed at the University of Minnesota. Two strata, based on the number of nucleated cells per kg recipient body weight (the 'dose') are monitored separately and different rules are constructed for each stratum using different prior distributions. It is believed that patients in the lower dose group have a greater chance of graft failure than those in the higher dose group. A program, written in R, is also presented for calculating the stopping rule using the prior beliefs. The program is an improvement upon existing programs and it can be used for larger studies.

Bayes Theorem↗

PubMed2006

First molecular data on the phylum Loricifera: an investigation into the phylogeny of ecdysozoa with emphasis on the positions of Loricifera and Priapulida.

Recent progress in molecular techniques has generated a wealth of information for phylogenetic analysis. Among metazoans all but a single phylum have been incorporated into some sort of molecular analysis. However, the minute and rare species of the phylum Loricifera have remained elusive to molecular systematists. Here we report the first molecular sequence data (nearly complete 18S rRNA) for a member of the phylum Loricifera, Pliciloricus sp. from Korea. The new sequence data were analyzed together with 52 other ecdysozoan sequences, with all other phyla represented by three or more sequences. The data set was analyzed using parsimony as an optimality criterion under direct optimization as well as using a Bayesian approach. The parsimony analysis was also accompanied by a sensitivity analysis. The results of both analyses are largely congruent, finding monophyly of each ecdysozoan phylum, except for Priapulida, in which the coelomate Meiopriapulus is separate from a clade of pseudocoelomate priapulids. The data also suggest a relationship of the pseudocoelomate priapulids to kinorhynchs, and a relationship of nematodes to tardigrades. The Bayesian analysis placed the arthropods as the sister group to a clade that includes tardigrades and nematodes. However, these results were shown to be parameter dependent in the sensitivity analysis. The position of Loricifera was extremely unstable to parameter variation, and support for a relationship of loriciferans to any particular ecdysozoan phylum was not found in the data.

Animals↗

PubMed2005

Cytochrome b and Bayesian inference of whale phylogeny.

In the mid 1990s cytochrome b and other mitochondrial DNA data reinvigorated cetacean phylogenetics by proposing many novel and provocative hypotheses of cetacean relationships. These results sparked a revision and reanalysis of morphological datasets, and the collection of new nuclear DNA data from numerous loci. Some of the most controversial mitochondrial hypotheses have now become benchmark clades, corroborated with nuclear DNA and morphological data; others have been resolved in favor of more traditional views. That major conflicts in cetacean phylogeny are disappearing is encouraging. However, most recent papers aim specifically to resolve higher-level conflicts by adding characters, at the cost of densely sampling taxa to resolve lower-level relationships. No molecular study to date has included more than 33 cetaceans. More detailed molecular phylogenies will provide better tools for evolutionary studies. Until more genes are available for a high number of taxa, can we rely on readily available single gene mitochondrial data? Here, we estimate the phylogeny of 66 cetacean taxa and 24 outgroups based on Cytb sequences. We judge the reliability of our phylogeny based on the recovery of several deep-level benchmark clades. A Bayesian phylogenetic analysis recovered all benchmark clades and for the first time supported Odontoceti monophyly based exclusively on analysis of a single mitochondrial gene. The results recover the monophyly of all but one family level taxa within Cetacea, and most recently proposed super- and subfamilies. In contrast, parsimony never recovered all benchmark clades and was sensitive to a priori weighting decisions. These results provide the most detailed phylogeny of Cetacea to date and highlight the utility of both Bayesian methodology in general, and of Cytb in cetacean phylogenetics. They furthermore suggest that dense taxon sampling, like dense character sampling, can overcome problems in phylogenetic reconstruction.

Animals↗

PubMed2005

Detecting small-area similarities in the epidemiology of childhood acute lymphoblastic leukemia and diabetes mellitus, type 1: a Bayesian approach.

Childhood acute lymphoblastic leukemia and diabetes mellitus, type 1, have common epidemiologic and etiologic features, including correlated international incidence and associations with infections. The authors examined whether the diseases' similar large-scale distributions are reflected in small geographic areas while also examining the influence of sociodemographic characteristics. Details of 299 children (0-14 years) with acute lymphoblastic leukemia and 1,551 children with diabetes diagnosed between 1986 and 1998 were extracted from two registers in Yorkshire, United Kingdom. Standardized incidence ratios across 532 electoral wards were compared using Poisson regression, confirming significant associations between population mixing and the geographic heterogeneity of both conditions. Bayesian methods analysis of spatial correlation between diseases by modeling a bivariate outcome based on their standardized incidence ratios was applied; spatial and heterogeneity components were included within a hierarchical random effects model. A positive correlation between diseases of 0.33 (95% credible interval: -0.20, 0.74) was observed, and this was reduced after control for population mixing (r = 0.18), population density (r = 0.14), and deprivation (r = 0.06). The Bayesian approach showed a modest but nonsignificant joint spatial correlation between diseases, only partially suggesting that the risk of both was associated within some electoral wards. With Bayesian methodology, population mixing remained significantly associated with both diseases. The links between diabetes and acute lymphoblastic leukemia observed for large regions are weaker for small areas. More powerful replications are needed for confirmation of these findings.

Adolescent↗

PubMed1999

Pharmacokinetics of (R)- and (S)-cyclophosphamide and their dechloroethylated metabolites in cancer patients.

The complete pharmacokinetics (PK) of (R)- and (S)-cyclophosphamide (CP) and their dechloroethylated (DCE) metabolites have not been reported to date. We collected plasma and urine samples from 12 cancer patients and determined concentrations of both enantiomers of CP and DCE-CP using a chiral GC-MS method. All concentrations of (R)-CP, (S)-CP, (R)-DCE-CP, and (S)-DCE-CP were simultaneously modeled using an enantiospecific compartmental PK model. A population PK analysis was performed. Enantiospecific differences between (R)- and (S)-CP were found for the formation clearance of CP to the DCE metabolites (Clf: 0.25 (R) vs. 0.14 (S) L/h). No difference was found between enantiomers for Cl40H, Cld, Cl(m)R, ClT, or T1/2. In contrast to the adolescent and adult group of patients, a child (6 years old) appeared to have a very different PK and metabolic profile (Bayesian control analysis). Proportions of the (R,S)-CP doses transformed to the (R)-DCE- and (S)-DCE-CP were much higher (R: 25 vs. 1.9%, and S: 38 vs. 3.6%), while formation of active metabolites was much lower (R: 42 vs. 74%, and S: 48 vs. 77%). CP appears to be enantioselectively metabolized to the DCE metabolites. This PK model can evaluate the proportion of a CP dose that is transformed to toxic or active metabolites. It may therefore be used to optimize CP treatment, to identify important drug interactions and/or patients with an abnormal metabolic profile.

Adolescent↗

PubMed2001

A statistical framework for quantitative trait mapping.

We describe a general statistical framework for the genetic analysis of quantitative trait data in inbred line crosses. Our main result is based on the observation that, by conditioning on the unobserved QTL genotypes, the problem can be split into two statistically independent and manageable parts. The first part involves only the relationship between the QTL and the phenotype. The second part involves only the location of the QTL in the genome. We developed a simple Monte Carlo algorithm to implement Bayesian QTL analysis. This algorithm simulates multiple versions of complete genotype information on a genomewide grid of locations using information in the marker genotype data. Weights are assigned to the simulated genotypes to capture information in the phenotype data. The weighted complete genotypes are used to approximate quantities needed for statistical inference of QTL locations and effect sizes. One advantage of this approach is that only the weights are recomputed as the analyst considers different candidate models. This device allows the analyst to focus on modeling and model comparisons. The proposed framework can accommodate multiple interacting QTL, nonnormal and multivariate phenotypes, covariates, missing genotype data, and genotyping errors in any type of inbred line cross. A software tool implementing this procedure is available. We demonstrate our approach to QTL analysis using data from a mouse backcross population that is segregating multiple interacting QTL associated with salt-induced hypertension.

Algorithms↗

PubMed2006

Mapping single-trial EEG records on the cortical surface through a spatiotemporal modality.

Event-related potentials (ERPs) induced by visual perception and cognitive tasks have been extensively studied in neuropsychological experiments. ERP activities time-locked to stimulus presentation and task performance are often observed separately at individual scalp channels based on averaged time series across epochs and experimental subjects. An analysis using averaged EEG dynamics could discount information regarding interdependency between ongoing EEG and salient ERP features. Advanced tools such as independent component analysis (ICA) have been developed for decomposing collections of single-trial EEG records into separate features. Those features (or independent components) can then be mapped onto the cortical surface using source localization algorithms to visualize brain activation maps and to study between-subject consistency. In this study, we propose a statistical framework for estimating the time course of spatiotemporally independent EEG components simultaneously with their cortical distributions. Within this framework, we implemented Bayesian spatiotemporal analysis for imaging the sources of EEG features on the cortical surface. The framework allows researchers to include prior knowledge regarding spatial locations as well as spatiotemporal independence of different EEG sources. The use of the Electromagnetic Spatiotemporal ICA (EMSICA) method is illustrated by mapping event-related EEG dynamics induced by events in a visual two-back continuous performance task. The proposed method successfully identified several interesting components with plausible corresponding cortical activation topographies, including processes contributing to the late positive complex (LPC) located in central parietal, frontal midline, and anterior cingulate cortex, to atypical mu rhythms associated with the precentral gyrus, and to the central posterior alpha activity in the precuneus.

Artifacts↗

PubMed2006

Is there a star tree paradox?

Concerns have been raised that posterior probabilities on phylogenetic trees can be unreliable when the true tree is unresolved or has very short internal branches, because existing methods for Bayesian phylogenetic analysis do not explicitly evaluate unresolved trees. Two recent papers have proposed that evaluating only resolved trees results in a "star tree paradox": when the true tree is unresolved or close to it, posterior probabilities were predicted to become increasingly unpredictable as sequence length grows, resulting in inflated confidence in one resolved tree or another and an increasing risk of false-positive inferences. Here we show that this is not the case; existing Bayesian methods do not lead to an inflation of statistical confidence, provided the evolutionary model is correct and uninformative priors are assumed. Posterior probabilities do not become increasingly unpredictable with increasing sequence length, and they exhibit conservative type I error rates, leading to a low rate of false-positive inferences. With infinite data, posterior probabilities give equal support for all resolved trees, and the rate of false inferences falls to zero. We conclude that there is no star tree paradox caused by not sampling unresolved trees.

Bayes Theorem↗

PubMed2004

Combination of direct and indirect evidence in mixed treatment comparisons.

Mixed treatment comparison (MTC) meta-analysis is a generalization of standard pairwise meta-analysis for A vs B trials, to data structures that include, for example, A vs B, B vs C, and A vs C trials. There are two roles for MTC: one is to strengthen inference concerning the relative efficacy of two treatments, by including both 'direct' and 'indirect' comparisons. The other is to facilitate simultaneous inference regarding all treatments, in order for example to select the best treatment. In this paper, we present a range of Bayesian hierarchical models using the Markov chain Monte Carlo software WinBUGS. These are multivariate random effects models that allow for variation in true treatment effects across trials. We consider models where the between-trials variance is homogeneous across treatment comparisons as well as heterogeneous variance models. We also compare models with fixed (unconstrained) baseline study effects with models with random baselines drawn from a common distribution. These models are applied to an illustrative data set and posterior parameter distributions are compared. We discuss model critique and model selection, illustrating the role of Bayesian deviance analysis, and node-based model criticism. The assumptions underlying the MTC models and their parameterization are also discussed.

Humans↗

PubMed2004

Single-copy nuclear genes recover cretaceous-age divergences in bees.

We analyzed the higher level phylogeny of the bee family Halictidae based on the coding regions of three single-copy nuclear genes (long-wavelength [LW] opsin, wingless, and elongation factor 1-alpha [EF-1 alpha]). Our combined data set consisted of 2,234 aligned nucleotide sites (702 base pairs [bp] for LW opsin, 405 bp for wingless, and 1,127 bp for EF-1 alpha) and 779 parsimony-informative sites. We included 58 species of halictid bees from 33 genera, representing all subfamilies and tribes, and rooted the trees using seven outgroups from other bee families: Colletidae, Andrenidae, Melittidae, and Apidae. We analyzed the separate and combined data sets by a variety of methods, including equal weights parsimony, maximum likelihood, and Bayesian methods. Analysis of the combined data set produced a strong phylogenetic signal with high bootstrap and Bremer support and high posterior probability well into the base of the tree. The phylogeny recovered the monophyly of the Halictidae and of all four subfamilies and both tribes, recovered relationships among the subfamilies and tribes congruent with morphology, and provided robust support for the relationships among the numerous genera in the tribe Halictini, sensu Michener (2000). Using our combined nucleotide data set, several recently described halictid fossils from the Oligocene and Eocene, and recently developed Bayesian methods, we estimated the antiquity of major clades within the family. Our results indicate that each of the four subfamilies arose well before the Cretaceous-Tertiary boundary and suggest that the early radiation of halictid bees involved substantial African-South American interchange roughly coincident with the separation of these two continents in the late Cretaceous. This combination of single-copy nuclear genes is capable of recovering Cretaceous-age divergences in bees with high levels of support. We propose that LW opsin, wingless, and EF-1 alpha(F2 copy) may be useful in resolving relationships among bee families and other Cretaceous-age insect lineages.

Animals↗

PubMed2002

Risk and uncertainty analysis in government safety decisions.

Probabilistic risk analysis (PRA) can be an effective tool to assess risks and uncertainties and to set priorities among safety policy options. Based on systems analysis and Bayesian probability, PRA has been applied to a wide range of cases, three of which are briefly presented here: the maintenance of the tiles of the space shuttle, the management of patient risk in anesthesia, and the choice of seismic provisions of building codes for the San Francisco Bay Area. In the quantification of a risk, a number of problems arise in the public sector where multiple stakeholders are involved. In this article, I describe different approaches to the treatments of uncertainties in risk analysis, their implications for risk ranking, and the role of risk analysis results in the context of a safety decision process. I also discuss the implications of adopting conservative hypotheses before proceeding to what is, in essence, a conditional uncertainty analysis, and I explore some implications of different levels of "conservatism" for the ranking of risk mitigation measures.

Journal Article↗

PubMed2003

Admixture analysis of South Asian cattle.

We present population genetic analysis of microsatellite variation in seven Bos indicus cattle breeds from a variety of locations in South Asia. This is the first such study focusing within this area, which is one of the postulated centres of origin of domestic cattle. An estimate of the influence of Bos taurus ancestry was carried out using three approaches: by the systematic selection of population-associated alleles for B. taurus and examination of their frequency; by examining the truncation of genetic distances from European populations; and by a model-based Bayesian admixture analysis. These analyses revealed a B. taurus influence in the Indian subcontinent; part of a gradation which stretches from Europe through the Near East towards Indian and which may be of ancient origin.

Alleles↗

PubMed2003

Data mining and computationally intensive methods: summary of Group 7 contributions to Genetic Analysis Workshop 13.

The Framingham Heart Study data, as well as a related simulated data set, were generously provided to the participants of the Genetic Analysis Workshop 13 in order that newly developed and emerging statistical methodologies could be tested on that well-characterized data set. The impetus driving the development of novel methods is to elucidate the contributions of genes, environment, and interactions between and among them, as well as to allow comparison between and validation of methods. The seven papers that comprise this group used data-mining methodologies (tree-based methods, neural networks, discriminant analysis, and Bayesian variable selection) in an attempt to identify the underlying genetics of cardiovascular disease and related traits in the presence of environmental and genetic covariates. Data-mining strategies are gaining popularity because they are extremely flexible and may have greater efficiency and potential in identifying the factors involved in complex disorders. While the methods grouped together here constitute a diverse collection, some papers asked similar questions with very different methods, while others used the same underlying methodology to ask very different questions. This paper briefly describes the data-mining methodologies applied to the Genetic Analysis Workshop 13 data sets and the results of those investigations.

Bayes Theorem↗

PubMed2024

Genetic investigation of population structure in Atlantic chub mackerel, Scomber colias Gmelin, 1789 along the West African coast.

Sustainable management of transboundary fish stocks hinges on accurate delineation of population structure. Genetic analysis offers a powerful tool to identify potential subpopulations within a seemingly homogenous stock, facilitating the development of effective, coordinated management strategies across international borders. Along the West African coast, the Atlantic chub mackerel (Scomber colias) is a commercially important and ecologically significant species, yet little is known about its genetic population structure and connectivity. Currently, the stock is managed as a single unit in West African waters despite new research suggesting morphological and adaptive differences. Here, eight microsatellite loci were genotyped on 1,169 individuals distributed across 33 sampling sites from Morocco (27.39°N) to Namibia (22.21°S). Bayesian clustering analysis depicts one homogeneous population across the studied area with null overall differentiation (F ST = 0.0001ns), which suggests panmixia and aligns with the migratory potential of this species. This finding has significant implications for the effective conservation and management of S. colias within a wide scope of its distribution across West African waters from the South of Morocco to the North-Centre of Namibia and underscores the need for increased regional cooperation in fisheries management and conservation.

Animals↗

PubMed2003

Tissue-specific gene expression of head and neck squamous cell carcinoma in vivo by complementary DNA microarray analysis.

OBJECTIVES: To identify distinct gene expression profiles of human head and neck squamous cell carcinomas (HNSCCAs) using complementary DNA (cDNA) microarray analysis and to create a preliminary, comprehensive database of HNSCCA gene expression. PATIENTS AND METHODS: Nine patients with histologically confirmed HNSCCAs, staged according to the American Joint Committee on Cancer, were enrolled. The HNSCCA tumor tissue and normal mucosal tissue were harvested at the time of surgery. A cDNA library was constructed from the paired fresh-frozen human surgical specimens of HNSCCAs and nonmalignant epithelial tissues. Biotinylated RNA was transcribed from the cDNA library and hybridized to high-density microarrays containing approximately 12 000 human genes. Altered gene expression of HNSCCAs was identified by comparison to corresponding normal mucosal tissues after a bayesian statistical analysis of variance. Results were analyzed using the gene database of the National Institutes of Health. Hierarchical clustering of the genomic data sets was determined by similarity metrics based on Pearson correlation. RESULTS: Hierarchical clustering analysis revealed that the gene expression profiles obtained from the nonselected panel of 12 000 genes could distinguish the tumors from nonmalignant tissues. Gene expression changes were reproducibly observed in 227 genes representing previously identified chemokines, tumor suppressors, differentiation markers, matrix molecules, membrane receptors, and transcription factors that correlated with neoplasia, including 46 previously uncharacterized genes. Moreover, significant expression of the collagen type XI alpha1 gene and a novel gene was reproducibly observed in all 9 tumors, whereas these genes were virtually undetectable in their corresponding, adjacent nonmalignant tissues. CONCLUSIONS: Complementary DNA microarray analysis of human HNSCCAs has produced a preliminary, comprehensive database of tumor-specific gene expression profiles and provided important insights into modeling gene expression changes implicated in carcinogenesis. A large-scale analysis of gene expression carries the future potential of identifying sensitive molecular markers for early tumor detection, prognosis, and novel targets for interceptive therapeutics.

Bayes Theorem↗

PubMed2006

Model for intracellular Lamivudine metabolism in peripheral blood mononuclear cells ex vivo and in human immunodeficiency virus type 1-infected adolescents.

The pharmacologic variability of nucleoside reverse transcriptase inhibitors such as lamivudine (3TC) includes not only systemic pharmacokinetic variability but also interindividual differences in cellular transport and metabolism. A modeling strategy linking laboratory studies of intracellular 3TC disposition with clinical studies in adolescent patients is described. Data from ex vivo laboratory experiments using peripheral blood mononuclear cells (PBMCs) from uninfected human subjects were first used to determine a model and population parameter estimates for 3TC cellular metabolism. Clinical study data from human immunodeficiency virus type 1-infected adolescents were then used in a Bayesian population analysis, together with the prior information from the ex vivo analysis, to develop a population model for 3TC systemic kinetics and cellular kinetics in PBMCs from patients during chronic therapy. The laboratory results demonstrate that the phosphorylation of 3TC is saturable under clinically relevant concentrations, that there is a rapid equilibrium between 3TC monophosphate and diphosphate and between 3TC diphosphate and triphosphate, and that 3TC triphosphate is recycled to 3TC monophosphate through a 3TC metabolite that remains to be definitively characterized. The resulting population model shows substantial interindividual variability in the cellular kinetics of 3TC with population coefficients of variation for model parameters ranging from 47 to 87%. This two-step ex vivo/clinical modeling approach using Bayesian population modeling of 3TC that links laboratory and clinical data has potential application for other drugs whose intracellular pharmacology is a major determinant of activity and/or toxicity.

Adolescent↗

PubMed2003

Statistical analysis of microarray data: a Bayesian approach.

The potential of microarray data is enormous. It allows us to monitor the expression of thousands of genes simultaneously. A common task with microarray is to determine which genes are differentially expressed between two samples obtained under two different conditions. Recently, several statistical methods have been proposed to perform such a task when there are replicate samples under each condition. Two major problems arise with microarray data. The first one is that the number of replicates is very small (usually 2-10), leading to noisy point estimates. As a consequence, traditional statistics that are based on the means and standard deviations, e.g. t-statistic, are not suitable. The second problem is that the number of genes is usually very large (approximately 10,000), and one is faced with an extreme multiple testing problem. Most multiple testing adjustments are relatively conservative, especially when the number of replicates is small. In this paper we present an empirical Bayes analysis that handles both problems very well. Using different parametrizations, we develop four statistics that can be used to test hypotheses about the means and/or variances of the gene expression levels in both one- and two-sample problems. The methods are illustrated using experimental data with prior knowledge. In addition, we present the result of a simulation comparing our methods to well-known statistics and multiple testing adjustments.

Algorithms↗

PubMed2024

Expansion of Oropouche virus in non-endemic Brazilian regions: analysis of genomic characterisation and ecological drivers.

BACKGROUND: Oropouche virus (OROV) is an arbovirus endemic in the Amazon region that closely resembles other arboviruses in terms of human disease, leading to potential misdiagnoses. The virus ecology has mostly restricted its occurrence to the Amazon biome; however, after a large 2023-24 OROV epidemic in the Brazilian Amazon region, outbreaks are being reported across Brazil and in other countries in Latin America. Here, we investigate the OROV spread outside Amazonia. METHODS: In this genomic and epidemiological study, OROV cases from January, 2023, to July, 2024, provided by the General Coordination of Public Health Laboratories of Brazil on Aug 1, 2024, were compared by geographical location (Amazon vs non-Amazon) and municipal population size, and a linear mixed model was employed to assess the relationship between agricultural area size and cases. OROV-positive samples from central laboratories of five non-Amazonian Brazilian states were sequenced using an amplicon-based approach. Bayesian phylogeographical analysis was performed with near full-length viral genomes, incorporating individual travel histories when relevant. The estimated dates of viral introductions in each sampled location were then contextualised with public epidemiological data. FINDINGS: Epidemic data show that outside the Amazon region, OROV cases frequency was 3·9-times higher in small municipalities than in large municipalities. The planted areas of some agricultural products, such as banana plantations, were positively correlated (r=0·39, p<0·0001) with OROV cases. The linear mixed model revealed that, besides banana, cassava also has larger (p<0·05) planted areas in municipalities with OROV cases when compared with those with no cases. The phylogenetic analysis of 32 new OROV genomes reconstructed multiple exportation events of the newly identified reassortant lineage from the Amazon to other Brazilian regions between January and March, 2024. At least three of the previously described OROV phylogenetic clades circulating in the Amazon were the source of viral introductions. Molecular clock analysis estimated that viral introductions happened from 50 days to 100 days before detecting the outbreaks in each state. INTERPRETATION: Our results confirm that the novel OROV reassortant lineage spread from the Amazon to other regions in early 2024, successfully establishing local transmission. The fact that outbreaks were observed in small municipalities, instead of large urban centres, suggests that local ecological conditions that are ideal for OROV vector occurrence, such as the banana plantation environment, might be important factors driving its spread in Brazil. FUNDING: DECIT, CNPq, FAPEAM, and Inova-Fiocruz. TRANSLATION: For the Portuguese translation of the abstract see Supplementary Materials section.

Brazil↗