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Results for “Bayesian analysis”

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PubMed2026

Bayesian Genome-Wide Association Study of Feed Efficiency Traits in Pigs.

Feed efficiency traits are increasingly important in pig production for improving profitability and environmental sustainability. Understanding their genetic basis is crucial for uncovering underlying biological mechanisms and informing selection strategies. In this study, we analyzed residual feed intake (RFI), feed conversion ratio (FCR), and average daily feed intake (ADFI) in 201 animals. Three separate Bayesian GWASs were conducted using 29,844 SNPs in a case-control design, with the lowest and highest 15% of the phenotypic distribution selected as controls and cases (N = 30 per group), respectively, for each trait. The results confirmed the polygenic nature of the traits, identifying 4 SNPs for RFI on Sus scrofa chromosomes (SSC) 3, 13, and 15 with high posterior probability for the direction of their effects; 4 SNPs for FCR on SSC 8, 14, and 17; and 8 SNPs for ADFI on SSC 1, 2, 6, 8, and 11. A candidate gene search identified 41 potential genes involved in diverse biological processes, including feed efficiency, intestinal development, tissue remodeling and integrity, nutrient transport and absorption, metabolic homeostasis, cellular signaling, energy sensing, and neurological regulation. These genes formed a highly interconnected network, highlighting the complexity of feed efficiency and the interplay among multiple physiological, metabolic, and regulatory pathways.

Bayesian analysis↗

PubMed2026

Multilevel genomic, transcriptomic, and epidemiologic evidence linking diabetic retinopathy to Alzheimer disease.

BACKGROUND: Diabetic retinopathy (DR) and Alzheimer disease (AD) share metabolic and vascular dysfunctions, but the extent to which they reflect overlapping genetic susceptibility and neurovascular-metabolic regulatory pathways remains unclear. We combined multi-omics analyses with population-based data to examine the genetic convergence, cellular pathways, and longitudinal association between DR and AD. METHODS: We performed a two-sample Mendelian randomisation (MR) to estimate the association between genetically predicted DR liability and AD risk. We used Bayesian colocalisation analysis to identify shared genomic loci, and summary-data-based MR (SMR) to detect expression-mediated genes jointly associated with DR and AD. We analysed single-cell RNA sequencing data to characterise shared cellular features and related biological pathways. We also conducted an MR-based mediation analysis to explore whether lipid-related, metabolic, or inflammatory traits mediated the observed DR-AD association, and a longitudinal analysis of the UK Biobank cohort to assess the association between DR and incident AD. RESULTS: With the MR analysis, we found that genetically predicted liability to DR was associated with a modest increase in AD risk. Colocalisation analysis supported a shared genetic signal. We identified three genes with shared expression-mediated associations across DR and AD through SMR. Functional enrichment analyses revealed partially overlapping neurovascular and metabolic pathways. Using MR-based mediation analysis, we found no significant intermediary traits linking DR and AD. Findings from the UK Biobank cohort were directionally consistent with the genetic analyses. CONCLUSIONS: Genetic liability to DR is associated with an increased risk of AD and is accompanied by shared expression-mediated effects and convergent neurovascular-metabolic pathways. These findings support the possibility that DR may serve as a clinically accessible indicator of increased neurodegenerative vulnerability.

Humans↗

PubMed2003

Tactile acuity is enhanced in blindness.

Functional imaging studies in blind subjects have shown tactile activation of cortical areas that normally subserve vision, but whether blind people have enhanced tactile acuity has long been controversial. We compared the passive tactile acuity of blind and sighted subjects on a fully automated grating orientation task and used multivariate Bayesian data analysis to determine predictors of acuity. Acuity was significantly superior in blind subjects, independently of the degree of childhood vision, light perception level, or Braille reading. Acuity was strongly dependent on the force of contact between the stimulus surface and the skin, declined with subject age, and was better in women than in men. Despite large intragroup variability, the difference between blind and sighted subjects was highly significant: the average blind subject had the acuity of an average sighted subject of the same gender but 23 years younger. The results suggest that crossmodal plasticity may underlie tactile acuity enhancement in blindness.

Adult↗

PubMed2005

Recent, allopatric, homoploid hybrid speciation: the origin of Senecio squalidus (Asteraceae) in the British Isles from a hybrid zone on Mount Etna, Sicily.

Homoploid hybrid speciation occurs through stabilization of a hybrid segregate (or segregates) isolated by premating and/or postmating barriers from parent taxa. Theory predicts that ecological and spatial isolation are of critical importance during homoploid hybrid speciation, and all confirmed homoploid hybrid species are ecologically isolated from their parents. Until recently, such species have been identified long after they originated, and consequently it has not been possible to determine the relative importance of spatial and ecological isolation during their origin. Here we present evidence for the recent origin (within the past 300 years) of a new homoploid hybrid species, Senecio squalidus (Asteraceae), in the British Isles, following long-distance dispersal of hybrid material from a hybrid zone between S. aethnensis and S. chrysanthemifolius on Mount Etna, Sicily, Italy. Historical records show that such hybrid material from Sicily was introduced to the Oxford Botanic Garden in Britain in the early part of the 18th century and that S. squalidus began to spread from there after approximately 90 years. A survey of randomly amplified polymorphic DNA/intersimple sequence repeats (RAPD/ISSR) marker variation demonstrated that S. squalidus is a diploid hybrid derivative of S. aethnensis and S. chrysanthemifolius that grow at high and low altitudes, respectively, on Mount Etna and that form a hybrid zone at intermediate altitudes. Senecio squalidus contained 11 of 13 RAPD/ISSR markers that were recorded at high frequency in S. chrysanthemifolius but were absent or occurred at low frequency in S. aethnensis, and 10 of 13 markers for which the reverse was true. Bayesian admixture analysis showed that all individuals of S. squalidus surveyed were of mixed ancestry with relatively high mean proportions of ancestry derived from both S. chrysanthemifolius and S. aethnensis (0.644 and 0.356, respectively). We argue that long-distance isolation of hybrid material from its parents on Mount Etna would have helped favor the origin and establishment of S. squalidus in the British Isles, regardless of whether the initial hybrid material introduced to Britain was preadapted to local conditions.

Altitude↗

PubMed1991

Analytical goals for determinations of theophylline concentration in serum.

Statistical principles for analytical goal-setting were applied to two medical applications of drug-monitoring data: (a) individualizing dosage requirements by reference to a population-based therapeutic range or to a patient-specific decision value determined by Bayesian decision analysis, and (b) prospective dosing by using pharmaco-kinetic principles. For application a, the analytical goal for total allowable analytical error (TE) was defined as the amount of error that does not decrease by more than 5% either the sensitivity (probability) for detecting dosage regimens that may require modification or the specificity for detecting appropriately dosed patients. The limiting factor in achievable sensitivity and specificity was the intra-individual variation of peak steady-state concentration (Css), with the TE determined to be a CV of 4%. For application b, error-propagation rules were applied to a proposed prospective dosing scheme (J Pharmacokinet Biopharm 1978;6:135-51). The TE was determined to depend on the rate of theophylline clearance. For clearance rates less than or equal to 0.6 mL/(kg.min), the TE (CV) must not exceed 3% if the predicted infusion rate is to produce, with 95% confidence, a concentration within the therapeutic range.

Humans↗

PubMed1988

A review on the methodology for assessing diagnostic tests.

Evaluation of diagnostic tests by the following principles are reviewed: error rates, scores based on posterior probabilities, and the excess loss considered in a decision theoretic context. Error rates or the complementary non-error rates, specificity and sensitivity, are simple measures which provide a rough indication of the discriminative value. In clinical practice, where a test serves as a decision support together with other information, conversion of test results to posterior probabilities is recommended. An aggregate score of these probabilities expresses the value of the test. Finally, in simple, well-defined cases--for example, screening situations, where the prevalence of disease and the relative consequences of false-positive and -negative classifications can be estimated--a Bayesian decision analysis is appropriate. The optimal discrimination limit is selected, and the total loss is minimized. The likelihood ratio LR(x) plays a central role in probability calculations and in the decision analysis. An example illustrates application of the procedures.

Algorithms↗

PubMed1987

Computer modeling of clinical judgment.

Four main developments leading to computer modeling of clinical judgment are described in this paper. These include information processing psychology, clinical vs. statistical prediction studies, behavioral decision theory, and Bayesian decision analysis approaches. One clear catalyst in these developments has been the computer, which has been used as an information management tool rather than a data-processing device. Future directions of these efforts are delineated, and problems as well as prospects of computerizing clinical judgment are described.

Artificial Intelligence↗

PubMed1983

[Immediate hypertensive flare-up after coronary bypass. A predictable complication].

An immediate post-operative rise in blood-pressure occurred in 44% of 191 patients undergoing coronary bypass. In a retrospective study of the patients' records, the authors have endeavoured to determine which of the 23 parameters characteristic of each patient was predictive of post-bypass hypertension. Using a Bayesian discriminant analysis method, they found that the only variables predictive of hypertension in 86% of the cases were an history of myocardial infarction and the urinary sodium/ potassium ratio. When combined, an urinary Na/K ratio below 1 and the absence of previous infarction constitute a good index of possible post-operative rise in blood pressure.

Coronary Artery Bypass↗

PubMed1995

A Bayesian model for growth curve analysis.

An experiment involves K subjects where for subject i, ni, values yi1, yi2, ..., y(ini) of a random variable Y are observed at times ti1 ti2, ..., t(ini). Assume that yij = F(tij) +eij where eij are independently and identically distributed (i.i.d.) N(0, sigma2). We consider the estimation of the function F and the testing of the homogeneity hypothesis that, for [formula, see text] does not depend on t. The function F(i,t) is modelled as a Gaussian process which seeks to quantify the notions that for each i, F(i, t) is a slowly changing function of t and that for i is not equal to j, F(i, t), and F(j, T) are in some sense similar. We propose to estimate F (i, t) by its posterior mean given all of the data. This Bayes estimate is shown to be equivalent to a particular form of penalised likelihood estimation. We consider data-based methods for setting the parameters of the Gaussian process prior, develop a test of the homogeneity hypothesis, report the results of a Monte Carlo study illustrating the effectiveness of the proposed methodology, and apply the methods to a study of variations in temperature and blood pressure over the course of the menstrual cycle.

Bayes Theorem↗

PubMed1994

Prediction of relapse in patients with breast cancer by DNA cytometry.

Nuclear DNA content was quantified for 193 ductal invasive breast carcinomas in a prospective study. The results were correlated with various clinical parameters. Of these tumours 66.2% were non-diploid and the incidence of non-diploid tumours is significantly higher in later stages of the disease. The median DNA values distribution tend to be bimodal, although in stage III a large number of cases showed DNA values between 2C and 4C. No association was observed between ploidy and menopause, lymph node status or incidence of recurrence. The mean times of relapse were 22.4 and 18.8 months in diploid and non-diploid groups, respectively. The present data suggest association between non-diploidy and tumour aggressiveness. Using Bayesian statistical analysis, the probability of the mean time of relapse in diploid group to be longer than in non-diploid group, given the data, is 0.875.

Bayes Theorem↗

PubMed2026

Umbilical Cord-Derived Cell-Based Interventions for Bronchopulmonary Dysplasia and Related Complications in Preterm Infants: A Bayesian Sparse-Data Meta-Analysis.

Bronchopulmonary dysplasia (BPD) is a major complication of prematurity with limited disease-modifying therapies. We evaluated umbilical cord-derived cell-based interventions for BPD and related complications in preterm infants. This Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020-based systematic review and meta-analysis were registered in PROSPERO. PubMed, Cochrane Library, Web of Science, CNKI, and Wanfang were searched from inception to June 14, 2026. Comparative clinical studies of umbilical cord-derived cell-based interventions in preterm infants at risk of or diagnosed with BPD were included. Outcomes included BPD, BPD severity, death, persistent pulmonary hypertension of the newborn (PPHN), patent ductus arteriosus (PDA), intraventricular hemorrhage (IVH), necrotizing enterocolitis (NEC), retinopathy of prematurity (ROP), late-onset sepsis (LOS), and adverse events (AEs). Bayesian random-effects meta-analysis used a binomial-normal hierarchical model to estimate pooled odds ratios (ORs), 95% credible intervals (CrIs), prediction intervals, and heterogeneity. Twelve studies were included. Umbilical cord-derived cell-based interventions showed a possible protective effect on overall BPD (OR, 0.48; 95% CrI, 0.14-1.20). Stronger associations were observed for severe BPD (OR, 0.17; 95% CrI, 0.01-0.85), moderate or severe BPD (OR, 0.28; 95% CrI, 0.09-0.70), and ROP stage ≥3 (OR, 0.17; 95% CrI, 0.02-0.65). No conclusive benefit or harm was observed for death, PPHN, PDA, IVH, NEC, or LOS. No treatment-related serious AEs were identified. However, prediction intervals were generally wide, and the certainty of evidence was low to very low for most outcomes. Umbilical cord-derived cell-based interventions may reduce the risk of moderate or severe BPD in preterm infants, with an additional potential benefit for ROP stage ≥3. Current evidence remains limited, and larger randomized trials with standardized outcomes and long-term follow-up are needed.

Humans↗

PubMed2003

Estimation of single-trial multicomponent ERPs: differentially variable component analysis (dVCA).

A Bayesian inference framework for estimating the parameters of single-trial, multicomponent, event-related potentials is presented. Single-trial recordings are modeled as the linear combination of ongoing activity and multicomponent waveforms that are relatively phase-locked to certain sensory or motor events. Each component is assumed to have a trial-invariant waveform with trial-dependent amplitude scaling factors and latency shifts. A Maximum a Posteriori solution of this model is implemented via an iterative algorithm from which the component's waveform, single-trial amplitude scaling factors and latency shifts are estimated. Multiple components can be derived from a single-channel recording based on their differential variability, an aspect in contrast with other component analysis techniques (e.g., independent component analysis) where the number of components estimated is equal to or smaller than the number of recording channels. Furthermore, we show that, by subtracting out the estimated single-trial components from each of the single-trial recordings, one can estimate the ongoing activity, thus providing additional information concerning task-related brain dynamics. We test this approach, which we name differentially variable component analysis (dVCA), on simulated data and apply it to an experimental dataset consisting of intracortically recorded local field potentials from monkeys performing a visuomotor pattern discrimination task.

Algorithms↗

PubMed2003

Application of a data-mining method based on Bayesian networks to lesion-deficit analysis.

Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.

Algorithms↗

PubMed2004

Applications of Bayesian statistical methods in microarray data analysis.

Microarray technology allows one to measure gene expression levels simultaneously on the whole-genome scale. The rapid progress generates both a great wealth of information and challenges in making inferences from such massive data sets. Bayesian statistical modeling offers an alternative approach to frequentist methodologies, and has several features that make these methods advantageous for the analysis of microarray data. These include the incorporation of prior information, flexible exploration of arbitrarily complex hypotheses, easy inclusion of nuisance parameters, and relatively well developed methods to handle missing data. Recent developments in Bayesian methodology generated a variety of techniques for the identification of differentially expressed genes, finding genes with similar expression profiles, and uncovering underlying gene regulatory networks. Bayesian methods will undoubtedly become more common in the future because of their great utility in microarray analysis.

Bayes Theorem↗

PubMed1990

The role of imaging in screening for prostate cancer. A decision analysis perspective.

Using Bayesian and decision analytical concepts, we can define the ideal characteristics of any screening test for cancer of the prostate: high specificity, reasonably high sensitivity, noninvasiveness, low cost, and low interobserver variability. Computed tomography (CT) fails as a test, since it cannot show the internal structure of the prostate; MRI is too expensive and has an unacceptably poor specificity. Transrectal sonography does have many desirable characteristics, including relatively high sensitivity and, if no biopsy is done, low cost and noninvasiveness. But it has an unacceptably low specificity for early, clinically significant lesions: over half of all patients tested will have a positive result, requiring a confirming biopsy, which means that transrectal sonography will in the end be too invasive and too expensive. Therefore, we cannot recommend transrectal sonography as a primary screening tool for cancer of the prostate at this time.

Costs and Cost Analysis↗

PubMed2004

Bayesian inference of the metazoan phylogeny; a combined molecular and morphological approach.

Metazoan phylogeny remains one of evolutionary biology's major unsolved problems. Molecular and morphological data, as well as different analytical approaches, have produced highly conflicting results due to homoplasy resulting from more than 570 million years of evolution. To date, parsimony has been the only feasible combined approach but is highly sensitive to long-branch attraction. Recent development of stochastic models for discrete morphological characters and computationally efficient methods for Bayesian inference has enabled combined molecular and morphological data analysis with rigorous statistical approaches less prone to such inconsistencies. We present the first statistically founded analysis of a metazoan data set based on a combination of morphological and molecular data and compare the results with a traditional parsimony analysis. Interestingly, the Bayesian analyses demonstrate a high degree of congruence between morphological and molecular data, and both data sets contribute to the result of the combined analysis. Additionally, they resolve several irregularities obtained in previous studies and show high credibility values for controversial groups such as the ecdysozoans and lophotrochozoans. Parsimony, on the contrary, shows conflicting results, with morphology being congruent to the Bayesian results and the molecular data set producing peculiarities that are largely reflected in the combined analysis.

Animals↗

PubMed1993

A case for Bayesianism in clinical trials.

This paper describes a Bayesian approach to the design and analysis of clinical trials, and compares it with the frequentist approach. Both approaches address learning under uncertainty. But they are different in a variety of ways. The Bayesian approach is more flexible. For example, accumulating data from a clinical trial can be used to update Bayesian measures, independent of the design of the trial. Frequentist measures are tied to the design, and interim analyses must be planned for frequentist measures to have meaning. Its flexibility makes the Bayesian approach ideal for analysing data from clinical trials. In carrying out a Bayesian analysis for inferring treatment effect, information from the clinical trial and other sources can be combined and used explicitly in drawing conclusions. Bayesians and frequentists address making decisions very differently. For example, when choosing or modifying the design of a clinical trial, Bayesians use all available information, including that which comes from the trial itself. The ability to calculate predictive probabilities for future observations is a distinct advantage of the Bayesian approach to designing clinical trials and other decisions. An important difference between Bayesian and frequentist thinking is the role of randomization.

Bayes Theorem↗

PubMed2004

SlidingBayes: exploring recombination using a sliding window approach based on Bayesian phylogenetic inference.

We developed a software tool (SlidingBayes) for recombination analysis based on Bayesian phylogenetic inference. Sliding-Bayes provides a powerful approach for detecting potential recombination, especially between highly divergent sequences and complex HIV-1 recombinants for which simpler methods like neighbor joining (NJ) may be less powerful. SlidingBayes guides Markov Chain Monte Carlo (MCMC) sampling performed by MrBayes in a sliding window across the alignment (Bayesian scanning). The tool can be used for nucleotide and amino acid sequences and combines all the modeling possibilities of MrBayes with the ability to plot the posterior probability support for clustering of various combinations of taxa.

Algorithms↗