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PubMed2005

Bayesian fMRI time series analysis with spatial priors.

We describe a Bayesian estimation and inference procedure for fMRI time series based on the use of General Linear Models (GLMs). Importantly, we use a spatial prior on regression coefficients which embodies our prior knowledge that evoked responses are spatially contiguous and locally homogeneous. Further, using a computationally efficient Variational Bayes framework, we are able to let the data determine the optimal amount of smoothing. We assume an arbitrary order Auto-Regressive (AR) model for the errors. Our model generalizes earlier work on voxel-wise estimation of GLM-AR models and inference in GLMs using Posterior Probability Maps (PPMs). Results are shown on simulated data and on data from an event-related fMRI experiment.

Bayes Theorem↗

PubMed2006

A Thurstonian model for quantitative genetic analysis of ranks: a Bayesian approach.

A fully Bayesian method for quantitative genetic analysis of data consisting of ranks of, e.g., genotypes, scored at a series of events or experiments is presented. The model postulates a latent structure, with an underlying variable realized for each genotype or individual involved in the event. The rank observed is assumed to reflect the order of the values of the unobserved variables, i.e., the classical Thurstonian model of psychometrics. Parameters driving the Bayesian hierarchical model include effects of covariates, additive genetic effects, permanent environmental deviations, and components of variance. A Markov chain Monte Carlo implementation based on the Gibbs sampler is described, and procedures for inferring the probability of yet to be observed future rankings are outlined. Part of the model is rendered nonparametric by introducing a Dirichlet process prior for the distribution of permanent environmental effects. This can lead to potential identification of clusters of such effects, which, in some competitions such as horse races, may reflect forms of undeclared preferential treatment.

Bayes Theorem↗

PubMed1997

Excitatory synaptic site heterogeneity during paired pulse plasticity in CA1 pyramidal cells in rat hippocampus in vitro.

1. The properties of individual excitatory synaptic sites onto adult CA1 hippocampal neurons were investigated using paired pulse minimal stimulation and low noise whole-cell recordings. Non-NMDA receptor-mediated synaptic responses were isolated using a pharmacological blockade of NMDA and GABAA receptors. Amongst the twenty-five stationary ensembles there were twelve showing paired pulse potentiation, two showing paired pulse depression and eleven with no significant net change. The signal-to-noise ratio averaged 4.5:1. There was no correlation between the amplitude of the first and second responses after separation of failures: the percentage of failures averaged 33.6% for the conditioning pulse and 31.7% for the test pulse. 2. Site-directed Bayesian statistical analysis was developed to predict the likely number of activated synapses, synaptic response amplitudes, probability of release and intrinsic variation at each individual synaptic site. Extensive simulations showed the usefulness of this model and defined appropriate parameters. These simulations demonstrated only small errors in estimating parameters of data sets with a small number of sites (< 10) and similar characteristics to the physiological data sets. 3. Physiological ensembles showed between one and three synaptic sites, which exhibited a wide range of values for release probability (0.03-0.99), synaptic amplitudes (1.46-16.8 pA; approximately 62% coefficient of variation between sites) and intrinsic variation over time (approximately 36%). Paired pulse plasticity occurred primarily from alterations in the release probabilities but a few ensembles also showed small changes in site amplitude. Initial release probability correlated negatively with the degree of paired pulse potentiation. Whilst it was possible to use simple assumptions regarding site homogeneity (such as required for a binomial process) for 48% (12 out of 25) of the data sets, the Bayesian analysis was necessary to reveal the complex changes and heterogeneity that occurred in the other 52% of the data sets. The Bayesian site analysis robustly indicated the presence of considerable site heterogeneity, significant intrinsic site variation over time and changes in parameters at individual synaptic sites with plasticity.

6-Cyano-7-nitroquinoxaline-2,3-dione↗

PubMed2006

Cross-species analysis of biological networks by Bayesian alignment.

Complex interactions between genes or proteins contribute a substantial part to phenotypic evolution. Here we develop an evolutionarily grounded method for the cross-species analysis of interaction networks by alignment, which maps bona fide functional relationships between genes in different organisms. Network alignment is based on a scoring function measuring mutual similarities between networks, taking into account their interaction patterns as well as sequence similarities between their nodes. High-scoring alignments and optimal alignment parameters are inferred by a systematic Bayesian analysis. We apply this method to analyze the evolution of coexpression networks between humans and mice. We find evidence for significant conservation of gene expression clusters and give network-based predictions of gene function. We discuss examples where cross-species functional relationships between genes do not concur with sequence similarity.

Algorithms↗

PubMed2003

Bayesian second-level analysis of functional magnetic resonance images.

We propose a new method for the second-level analysis of functional MRI data based on Bayesian statistics. Our method does not require a computationally costly Bayesian model on the first level of analysis. Rather, modeling for single subjects is realized by means of the commonly applied General Linear Model. On the basis of the resulting parameter estimates for single subjects we calculate posterior probability maps and maps of the effect size for effects of interest in groups of subjects. A comparison of this method with the conventional analysis based on t statistics shows that the new approach is more robust against outliers. Moreover, our method overcomes some of the severe problems of null hypothesis significance tests such as the need to correct for multiple comparisons and facilitates inferences which are hard to formulate in terms of classical inferences.

Algorithms↗

PubMed1984

Use of a Bayesian algorithm in the computer-assisted diagnosis of appendicitis.

One hundred consecutive patients with acute right lower quadrant abdominal pain were prospectively evaluated with a computerized Bayesian diagnostic algorithm. An accuracy rate of 92 per cent was obtained. Computer recommendations would have resulted in a negative exploration rate of 9 per cent, as compared with the rate of 19 per cent which was actually obtained. Even though our clinical management of these patients was in keeping with accepted standards, the Bayesian program would have avoided eight unnecessary operations. In all instances in which the patient presented with appendicitis, the computer correctly predicted that appendicitis was present. Computer-assisted diagnostic programs using a Bayesian approach may have some role in the evaluation of right lower quadrant abdominal pain. The technique presented herein describes a means of developing a database of conditional probabilities without reliance on large patient surveys. Even with this refinement, the Bayesian approach to diagnosis remains complex. The development of this type of program requires close interaction between computer scientists and surgeons. Nevertheless, the approach does appear promising and it may well be worth the considerable effort required to initiate such a system. The exact role for Bayesian diagnostic analysis cannot be predicted at this point. Certainly it should have no greater importance than a routine laboratory test. Perhaps the results of Bayesian analysis in this setting might assume a diagnostic significance similar to that of the white blood cell count. The work of DeDombal has done much to eliminate the physician reluctance seen with earlier programs. It has become increasingly apparent that computers may perform many clinically useful functions without infringing upon the art of medicine. The computer assisted diagnosis of acute abdominal pain may well constitute one such function.

Acute Disease↗

PubMed2004

Bayesian approaches for the analysis of population genetic structure: an example from Platanthera leucophaea (Orchidaceae).

We describe four extensions to existing Bayesian methods for the analysis of genetic structure in populations: (i) use of beta distributions to approximate the posterior distribution of f and theta(B); (ii) use of an entropy statistic to describe the amount of information about a parameter derived from the data; (iii) use of the Deviance Information Criterion (DIC) as a model choice criterion for determining whether there is evidence for inbreeding within populations or genetic differentiation among populations; and (iv) use of samples from the posterior distributions for f and theta(B) derived from different data sets to determine whether the estimates are consistent with one another. We illustrate each of these extensions by applying them to data derived from previous allozyme and random amplified polymorphic DNA surveys of an endangered orchid, Platanthera leucophaea, and we conclude that differences in theta(B) from the two data sets may represent differences in the underlying mutational processes.

Bayes Theorem↗

PubMed2006

A systematic review of the quality of genetic association studies in human sepsis.

OBJECTIVE: Epidemiological studies demonstrate that inherited factors play a major role in the development and prognosis of sepsis. However, genetic association studies in sepsis have produced contradictory evidence of an effect from individual polymorphisms. Major methodological flaws have been reported in a number of genetic association studies in non-septic populations, relating to problems with experimental design, statistical analysis, study size, power and replication. We hypothesised that genetic association studies investigating sepsis suffer from similar problems, and that this explains the lack of consistent evidence for an effect from polymorphisms. DESIGN: A systematic review was conducted of published genetic association studies in sepsis from 1996-2005 using a newly devised scoring system for study quality and rigour. A Bayesian statistical analysis was also carried out to assess the false-positive report probability of identified studies. MEASUREMENTS AND RESULTS: Study quality was assessed using a 10-point scoring system designed from published reporting guidelines. The majority of studies were of low to intermediate quality, with deficiencies in control group selection, genetic assay technique, study blinding, statistical interpretation, study replication, study size and power. Bayesian analysis indicated that many of the studies reporting a positive association between a genetic polymorphism and sepsis were likely to represent false-positive associations. CONCLUSIONS: The quality and size of genetic association studies in septic patients needs to improve if advances in identifying genetic effects in sepsis are to occur. Investigators should, as a minimum, follow recommended guidelines when designing studies.

Evidence-Based Medicine↗

PubMed2002

Classic or Bayesian research design and analysis. Does it make a difference?

OBJECTIVE: The role of classical and Bayesian statistical approaches remains in dispute in health services research and policy. The goal of this study was to determine if results differ when both analytic techniques are used with the same data set. DESIGN: We searched MEDLINE and related databases for English-language articles published January 1, 1978 through August 31, 1999. We combined Bayesian and classical statistics search terms and their variants with randomized control trials (RCTs) and meta-analyses. RESULTS: Searches found 18 studies in 14 publications that met all review criteria--nine RCTs, eight meta-analyses, and one epidemiologic estimate. Statistical analyses using both methods agreed in five RCTs, four meta-analyses, and for the epidemiologic estimates. For four RCTs where results disagreed, classical analysis found the experimental intervention was efficacious compared with the control, and Bayesian reanalysis concluded the intervention was not proven efficacious. Classical meta-analyses of the four studies where results disagreed concluded the experimental intervention was not better than the control; Bayesian reanalysis concluded it was efficacious. CONCLUSION: Classical and Bayesian methods in this review exhibited important divergence of results. Disagreement on many fundamental beliefs between classical and Bayesian statistics means continuing debate. One way to resolve this debate is for proponents of each technique to decide together the circumstances for use of each method and analytic framework. If the experts do not agree on the methodologic requirements, other decision makers likely will force their own views.

Bayes Theorem↗

PubMed2006

Bayesian cost-effectiveness analysis with two measures of effectiveness: the cost-effectiveness acceptability plane.

Cost-effectiveness analysis (CEA) compares the costs and outcomes of two or more technologies. However, there is no consensus about which measure of effectiveness should be used in each analysis. Clinical researchers have to select an appropriate outcome for their purpose, and this choice can have dramatic consequences on the conclusions of their analysis. In this paper we present a Bayesian cost-effectiveness framework to carry out CEA when more than one measure is considered. In particular, we analyse the case in which two measures of effectiveness, one binary and the other continuous, are considered. Decision-making measures, such as the incremental cost-effectiveness ratio, incremental net-benefit and cost-effectiveness acceptability curves, are used to compare costs and one measure of outcome. We propose an extension of cost-acceptability curves, namely the cost-effectiveness acceptability plane, as a suitable measure for decision taking. The models were validated using data from two clinical trials. In the first one, we compared four highly active antiretroviral treatments applied to asymptomatic HIV patients. As measures of effectiveness, we considered the percentage of patients with undetectable levels of viral load, and changes in quality of life, measured according to EuroQol. In the second clinical trial we compared three methadone maintenance programmes for opioid-addicted patients. In this case, the measures of effectiveness considered were quality of life, according to the Nottingham Health Profile, and adherence to the treatment, measured as the percentage of patients who participated in the whole treatment programme.

Anti-Retroviral Agents↗

PubMed2026

Suction-assisted ureteroscopy compared with traditional ureteroscopy for renal stones ≤ 2 cm: a systematic review, Bayesian network meta-analysis and meta-regression.

INTRODUCTION AND OBJECTIVE: Suction-enhanced flexible ureteroscopy (URS) aims to improve stone clearance and reduce complications. We performed a Bayesian network meta-analysis to compare the efficacy and safety of flexible aspiration navigable sheaths (FANS) and direct in-scope suction (DISS) for renal calculi ≤ 2 cm. METHODS: A systematic search of PubMed, MEDLINE, Scopus, Web of Science, and Google Scholar was conducted through June 2026. Comparative studies of FANS, DISS, or conventional access sheaths for renal stones ≤ 2 cm were included. The primary outcome was 30-day stone-free rate (SFR). Secondary outcomes included operative time, fever, sepsis, and complications. A Bayesian random-effects network meta-analysis synthesized direct and indirect evidence. RESULTS: Seventeen studies including 3,657 patients (1,677 FANS, 56 DISS, 1,924 control) were included. FANS showed higher SFR (OR 2.5, 95% CrI 2.0-3.1), while grouped DISS had a similar but less precise effect (OR 3.1, 95% CrI 1.0-8.8). Calyxo V2 had the highest SFR (OR 5.4, 95% CrI 1.0-29.0), whereas PUSEN showed no significant difference (OR 1.6, 95% CrI 0.41-6.3). FANS reduced postoperative fever and complications. FANS also showed lower odds of postoperative sepsis (OR 0.40, 95% CrI 0.12-0.97). CONCLUSIONS: Suction-assisted ureteroscopy improves SFR for renal calculi ≤ 2 cm. FANS was associated with shorter operative time, fever, and complications. DISS systems show promising but limited results, with performance differing by technology configuration. Larger prospective trials are needed.

Humans↗

PubMed2002

Planning the efficient allocation of research funds: an adapted application of a non-parametric Bayesian value of information analysis.

The issue of the efficient allocation of research funds has been addressed using various quantitative methods. Bayesian value of information (VoI) analysis provides an explicit and comprehensive analytic process for the comparison of alternative sources of research. This paper presents an adapted non-parametric application of a VoI analysis of prospective trials comparing alternative adjuvant therapies for postmenopausal women with node positive early breast cancer. The results show that such trials would produce substantial net benefits, though the extent of the net benefits is clearly influenced by the assumed length of usefulness of the research. The application of the VoI methodology shows that such analyses are practical and the recent increase in the use of stochastic decision models in the economic evaluation of health care technologies facilitates further applications of VoI analyses to inform the allocation of research funds.

Aged↗

PubMed2001

Bayesian methods in meta-analysis and evidence synthesis.

This paper reviews the use of Bayesian methods in meta-analysis. Whilst there has been an explosion in the use of meta-analysis over the last few years, driven mainly by the move towards evidence-based healthcare, so too Bayesian methods are being used increasingly within medical statistics. Whilst in many meta-analysis settings the Bayesian models used mirror those previously adopted in a frequentist formulation, there are a number of specific advantages conferred by the Bayesian approach. These include: full allowance for all parameter uncertainty in the model, the ability to include other pertinent information that would otherwise be excluded, and the ability to extend the models to accommodate more complex, but frequently occurring, scenarios. The Bayesian methods discussed are illustrated by means of a meta-analysis examining the evidence relating to electronic fetal heart rate monitoring and perinatal mortality in which evidence is available from a variety of sources.

Bayes Theorem↗

PubMed2000

Bayesian linkage and segregation analysis: factoring the problem.

Complex segregation analysis and linkage methods are mathematical techniques for the genetic dissection of complex diseases. They are used to delineate complex modes of familial transmission and to localize putative disease susceptibility loci to specific chromosomal locations. The computational problem of Bayesian linkage and segregation analysis is one of integration in high-dimensional spaces. In this paper, three available techniques for Bayesian linkage and segregation analysis are discussed: Markov Chain Monte Carlo (MCMC), importance sampling, and exact calculation. The contribution of each to the overall integration will be explicitly discussed.

Bayes Theorem↗

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↗

PubMed2006

Gene expression profiling of whole-blood samples from women exposed to hormone replacement therapy.

The American Women's Health Initiative study published in July 2002 caused considerable concern among hormone replacement therapy (HRT) users and prescribers in many countries. This study is an exploratory research comparing the genome-wide expression profile in whole-blood samples according to HRT use. Within the Norwegian Women and Cancer study, 100 postmenopausal women (50 HRT users and 50 non-HRT users) born between 1943 and 1949 with normal to high body mass index and no other medication use were selected. After total RNA extraction, amplification, and labeling, the samples were hybridized together with a common reference (Universal human reference RNA, Stratagen) to Agilent Human 1A oligoarrays (G4110b, Agilent Technologies) containing 20,173 unique genes. Differentially expressed genes were used to build a classifier using the nearest shrunken centroid method (PAM). Then, we tested the significant changes in single genes by different methods like t test, Significance Analysis of Microarrays, and Bayesian ANOVA analysis. Results did not reveal any distinct gene list which predicted accurately HRT exposure (error rate, 0.40). Classifier performance slightly improved (error rate, 0.26) including only women who were using continuous combined HRT treatment. According to the small amplitude of expression alterations observed in whole blood, more quantitative technique and larger sample sizes will be needed to be able to investigate whether significant single genes are differentially expressed in HRT versus non-HRT users. Taken cautiously, significant enrichments in biological process of genes with small changes after HRT use were observed (e.g., receptor and transporter activities, immune response, frizzled signaling pathway, actin filament organization, and glycogen metabolism).

Adult↗

PubMed2006

Determination of strongly overlapping signaling activity from microarray data.

BACKGROUND: As numerous diseases involve errors in signal transduction, modern therapeutics often target proteins involved in cellular signaling. Interpretation of the activity of signaling pathways during disease development or therapeutic intervention would assist in drug development, design of therapy, and target identification. Microarrays provide a global measure of cellular response, however linking these responses to signaling pathways requires an analytic approach tuned to the underlying biology. An ongoing issue in pattern recognition in microarrays has been how to determine the number of patterns (or clusters) to use for data interpretation, and this is a critical issue as measures of statistical significance in gene ontology or pathways rely on proper separation of genes into groups. RESULTS: Here we introduce a method relying on gene annotation coupled to decompositional analysis of global gene expression data that allows us to estimate specific activity on strongly coupled signaling pathways and, in some cases, activity of specific signaling proteins. We demonstrate the technique using the Rosetta yeast deletion mutant data set, decompositional analysis by Bayesian Decomposition, and annotation analysis using ClutrFree. We determined from measurements of gene persistence in patterns across multiple potential dimensionalities that 15 basis vectors provides the correct dimensionality for interpreting the data. Using gene ontology and data on gene regulation in the Saccharomyces Genome Database, we identified the transcriptional signatures of several cellular processes in yeast, including cell wall creation, ribosomal disruption, chemical blocking of protein synthesis, and, critically, individual signatures of the strongly coupled mating and filamentation pathways. CONCLUSION: This works demonstrates that microarray data can provide downstream indicators of pathway activity either through use of gene ontology or transcription factor databases. This can be used to investigate the specificity and success of targeted therapeutics as well as to elucidate signaling activity in normal and disease processes.

Algorithms↗

PubMed2026

Ventriculostomy-Related Infections by Country-Income Level: A Systematic Review and Bayesian Hierarchical Meta-analysis.

Our objective was to perform a systematic review and meta-analysis of published literature on ventriculostomy-related infection (VRI) and evaluate temporal and global trends. We conducted a systematic review and Bayesian hierarchical random-effects meta-analysis of VRI rates in adults, stratified by country-income level (high-income countries [HIC]; low- or middle-income countries [LMIC]), study design, sample size, enrollment period, VRI intervention, and VRI definition. We identified 159 articles published between 1989 and 2025 that included 523,704 patients with 7293 VRIs. The pooled VRI rate was 8.64% [95% CI: 7.44-9.97], with moderate heterogeneity and good model fit. The leave-one-out sensitivity analysis showed a mean absolute change of 0.06% and a maximum change of 0.2%, indicating robust analysis. Five of the 33 represented countries had VRI rates below the global pooled rate of 8.64%. Four were HICs: Singapore (VRI rate 3.3% [0.8-7]), the United States (VRI rate 4.6% [3.4-5.9]), Germany (VRI rate 6.1% [1.1-18.9]), Norway (8.3% [0.3-68.4]), with 1 LMIC: China (8.5% [5.4-12.4]). VRI was significantly higher in studies using definitions beyond CSF culture alone for VRI (+3.16% [0.11- 6.52]) and in those from Europe (+7.29% [4.62-10.10]) and the Western Pacific (+4.09% [1.55-6.98]). No other subgroup demonstrated significant differences. This Bayesian meta-analysis provides global estimates and factors associated with VRI. Standardization of VRI definitions is critical for future benchmarking of VRI rates.

Humans↗