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Results for “Bootstrap resampling”

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PubMed2006

A prognostic model for functional outcome in early rheumatoid arthritis.

OBJECTIVE: To construct a prognostic algorithm to predict 5-year functional outcome in rheumatoid arthritis (RA), based on the Health Assessment Questionnaire (HAQ). METHODS: Data from all patients with 5-year followup (n = 985) were used from an inception cohort, the Early Rheumatoid Arthritis Study (ERAS). Possibly relevant prognostic factors considered in the initial stage of the model-building process were standard clinical, radiological, and laboratory features measured at baseline and at 1 year. Multivariate analysis was performed using logistic regression, and the predictive performance of the model was tested using measures of discrimination and calibration. RESULTS: Bootstrap resampling identified 6 variables that consistently predicted severe functional outcome. Functional grade III/IV (odds ratio 6.7) and HAQ at 1 year (odds ratio 2.4) were the most important. Other variables included socioeconomic status, hemoglobin, and radiographic and disease activity scores. Estimates of the regression coefficients and performance were corrected for over-fitting. Reasonably large values for the c-index (0.82) and the Nagelkerke R(2) (0.39) indicate that the set of prognostic factors explains the variation in outcome to a degree that implies good prediction for individual patients. CONCLUSION: The algorithm identifies patients in the first year of RA who are likely to have poor function by 5 years and who could potentially benefit from aggressive drug therapy. A nomogram is produced for simple application of the model in clinical practice. While further external validation is necessary, this model could allow clinicians to target aggressive therapy earlier in a patient's disease course.

Adult↗

PubMed1994

Relationships of G-protein-coupled receptors. A survey with the photoreceptor opsin subfamily.

Relationships among the G-protein-coupled receptors were evaluated using several distance matrices with the neighbor-joining method of Saitou and Nei (1987). The relationships generated vary depending upon alignment, length, or region of sequence compared, and the distance matrix used to score similarity. To provide a statistical level of confidence, bootstrap resampling was applied to the analysis of a selection of G-protein-coupled receptors and the subfamily photoreceptor opsins. A general consensus indicates that the opsins behave as a discrete subfamily among the superfamily of G-protein-coupled receptors. Their relationship to other subfamilies remains unresolved. Within the opsin subfamily, the retinochromelike opsins segregate as a discrete group, but are more closely related to the invertebrate than vertebrate opsins. Among vertebrate opsins, the long wavelength cone opsins, the blue/violet opsins, and the rod opsins (including a class of green cone opsins) form distinct subgroups, but their relationships to one another remain unresolved. For this superfamily of receptors, the confidence levels for many branch pairings are low. The application of methods complimentary to those used in this preliminary study will be necessary to resolve questions about appropriate pairing and evolutionary relationships.

Amino Acid Sequence↗

PubMed1994

Predicting orthostatic intolerance: physics or physiology?

To adequately assess the viability of any particular causal theory of orthostatic intolerance, physical and physiological parameters thought to be associated with orthostasis must be evaluated simultaneously within the same individual. Time, cost, and complexity of instrumentation generally limit studies of orthostatic intolerance to a single independent effect for any given sample of subjects. We, therefore, measured 6 key physical and physiological variables associated with various theories of orthostatic intolerance in 14 males to test the hypothesis that physical factors rather than physiological reflex mechanisms were dominant in contributing to orthostatic tolerance. Measurements included height, plasma volume (expressed as percent of total weight), variation in R-R interval, leg compliance, and carotid-cardiac (high pressure), and cardiopulmonary (low pressure) baroreflex sensitivity. Subjects' orthostatic intolerance was quantified by time to syncope during progressive supine lower body decompression. Correlations, regression coefficients, and indices of replicability were calculated using 500 to 1,000 bootstrap resamplings of the original 14 observations. Although all six measurements correlated with time to syncope when evaluated individually, only height (negative), percent plasma volume weight (positive), and, to a lesser extent, carotid-cardiac baroreflex sensitivity yielded consistent (reproducible) results when all measures were tested simultaneously. These results suggest that while orthostatic intolerance may be dependent upon a variety of physiological reflexes, physical factors such as height and plasma volume tend to dominate the prediction of time to syncope during lower body negative pressure (LBNP). Physiological reflexes, which act to maintain adequate profusion to the brain during normal terrestrial posture in humans, may be overwhelmed by the additional orthostatic challenge imposed by progressive lower body decompression.

Adult↗

PubMed1996

Molecular phylogeny of Schistosoma species supports traditional groupings within the genus.

Phylogenetic relationships among 9 blood flukes (7 schistosome species, a spirorchid, and a sanguinicolid) were inferred from nucleotide sequences of the D1 domain of large subunit rRNA and the V4 region of small subunit rRNA. These sequences were more conserved than those examined by previous authors and thus may provide insight into deeper-level relationships. Analyzed separately and combined by 3 methods, these data yielded congruent trees that were well supported by bootstrap resampling. The traditional groups of schistosome species based on egg type were supported. Schistosoma japonicum and Schistosoma mekongi were distinct from the remaining Schistosoma species. Schistosoma spindale (from India and southeast Asia) clustered strongly with the African species to the exclusion of the other Asian species, S. japonicum and S. mekongi. Schistosoma spindale may have been brought to India and southeast Asia from Africa by early humans. Statistical tests revealed only weak evidence for the operation of a molecular clock in the V4 sequence; no evidence was found for this in the D1 domain.

Africa↗

PubMed1998

Gamma-ray mutagen sensitivity and survival in patients with glioma.

Despite advances in treatment of brain tumors, cerebral malignant gliomas are rapidly debilitating with poor survival. Patient age and tumor histology are known to influence survival in glioma patients, but these factors do not account for all of the variability in survival time. To identify additional useful predictors, we tested an assay that measures intrinsic gamma-ray mutagen sensitivity. Our hypothesis was that increased sensitivity of peripheral blood lymphocytes to chromatid breaks is associated with tumor aggressiveness and decreased patient survival. The eligible 76 patients were those with histologically confirmed malignant gliomas, seen at the University of Texas M. D. Anderson Cancer Center between 1994 and 1997, for whom we had sufficient blood for the in vitro gamma-radiation assay. After gamma-irradiation of each subject's lymphocytes, the frank chromatid breaks in 50 metaphases were averaged to calculate breaks/cell. On the basis of our patient series, we established a gamma-ray mutagen sensitivity cutoff point of 0.55 breaks/cell that was confirmed by bootstrap resampling techniques. Patients with values >0.55 breaks/cell were considered sensitive. Kaplan-Meier and Cox proportional hazards modeling were used for the analysis. The gamma-ray mutagen-sensitive patients had worse survival than the nonsensitive patients, with an unadjusted hazard rate ratio of 1.6 (95% confidence interval, 0.9-2.8; P = 0.15). After adjustment for age, tumor histology, and extent of surgical resection, the hazard rate ratio was 2.4 (95% confidence interval, 1.3-4.6; P = 0.0081). Our data suggest that gamma-ray mutagen sensitivity is a prognostic indicator of survival in glioma patients. The significance of these findings needs to be verified in studies with larger samples of patients with histologically similar gliomas.

Adult↗

PubMed1998

Piecewise exponential survival trees with time-dependent covariates.

Survival trees methods are nonparametric alternatives to the semiparametric Cox regression in survival analysis. In this paper, a tree-based method for censored survival data with time-dependent covariates is proposed. The proposed method assumes a very general model for the hazard function and is fully nonparametric. The recursive partitioning algorithm uses the likelihood estimation procedure to grow trees under a piecewise exponential structure that handles time-dependent covariates in a parallel way to time-independent covariates. In general, the estimated hazard at a node gives the risk for a group of individuals during a specific time period. Both cross-validation and bootstrap resampling techniques are implemented in the tree selection procedure. The performance of the proposed survival trees method is shown to be good through simulation and application to real data.

Biometry↗

PubMed2001

Fungal Zuotin proteins evolved from MIDA1-like factors by lineage-specific loss of MYB domains.

Proteins are often characterized by the presence of multiple domains, which make specific contributions to their cellular function. While the gain of domains in proteins by duplication and shuffling is well established, domain loss is poorly documented. Here, we provide evidence that domain loss has played an important role in the evolution of protein architecture and function by demonstrating that fungal Zuotin proteins evolved from MIDA1-like proteins, present in animals and plants, by complete loss of the carboxyl-terminal MYB domains. Phylogenetic analyses of the DnaJ motif (the J domain) present in both Zuotin and MIDA1 proteins were complicated by the limited length and profound differences in evolutionary rates exhibited by this domain. To rigorously examine J domain phylogeny, we combined the nonparametric bootstrap with Monte Carlo simulation. This method, which we have designated the resampled parametric bootstrap, allowed us to assess type I and type II error associated with these analyses. These results revealed significant support for domain loss rather than domain gain or gene loss involving paralogs. The absence of sequences related to the MIDA1 MYB domains in Saccharomyces cerevisiae further indicates that the domains have been completely lost, consistent with known functional differences between Zuotin and MIDA1 proteins. These analyses suggest that the description of additional examples of complete domain loss may provide a method to identify orthologous proteins exhibiting functional differences using genomic sequence data.

Amino Acid Sequence↗

PubMed2005

Resampling methods to reduce the selection bias in genetic effect estimation in genome-wide scans.

Using the simulated data of Problem 2 for Genetic Analysis Workshop 14 (GAW14), we investigated the ability of three bootstrap-based resampling estimators (a shrinkage, an out-of-sample, and a weighted estimator) to reduce the selection bias for genetic effect estimation in genome-wide linkage scans. For the given marker density in the preliminary genome scans (7 cM for microsatellite and 3 cM for SNP), we found that the two sets of markers produce comparable results in terms of power to detect linkage, localization accuracy, and magnitude of test statistic at the peak location. At the locations detected in the scan, application of the three bootstrap-based estimators substantially reduced the upward selection bias in genetic effect estimation for both true and false positives. The relative effectiveness of the estimators depended on the true genetic effect size and the inherent power to detect it. The shrinkage estimator is recommended when the power to detect the disease locus is low. Otherwise, the weighted estimator is recommended.

Chromosome Mapping↗

PubMed1995

Use of resampling techniques to estimate the variance of parameters in pharmacological assays when experimental protocols preclude independent replication: an example using Schild regressions.

Estimates of variance in pharmacological assays are usually made by repeating the experiment with different tissues. Biological factors, such as the inability to wash a drug from tissue, may preclude the type of replication that is appropriate for the statistics of interest. For example, in Schild regressions, replication is usually done at each concentration of antagonist. In some test systems, replication of dose-response curves is not possible. For example, some persistent agonists cannot be removed from tissues after exposure, while in other systems, rapid desensitization severely alters tissue sensitivity to repeated challenge with agonist. In this paper, we demonstrate how a statistical resampling method, bootstrapping, can be used to derive estimates of the confidence intervals for pA2, pKB, and slope from Schild plots. This method utilizes the speed of the computer to estimate variance by repeatedly resampling the data. The advantage to this method is that it can be used for many different experimental designs. For a data set obtained from a Schild regression of atenolol antagonism of isoproterenol in the guinea pig left atrium, bootstrap estimates of confidence limits were calculated for cases where dose ratios were derived from the same tissue and randomly paired tissues. These estimates showed good agreement with estimates obtained using conventional analytical methods, thus suggesting that this method may be useful in practice.

Adrenergic beta-Agonists↗

PubMed2004

Analysis of histamine release assays using the Bootstrap.

The data from several types of bioassays is usually presented as a quotient as an intuitive parameter and a means of comparing results between experiments. For the example we considered here, we look at experiments with an experiment-wide negative control used to generate percent activity quotients from each experimental group. We asked if there was a valid means to statistically evaluate the transformed rather than the raw data. The experimental system chosen was a dose response of the agonist compound 48/80, which causes release of histamine from mast cells, thus providing test data from replicates of n=24. Descriptive statistics, the Ryan-Joiner test for normality of distribution of data, and normal probability plots confirm the normality of the distribution of data at each dose level. In parametric analysis, when the control group was treated as an errorless constant, there was a distinct consistent bias in the standard error of the data of 10% or less, which was not present if the control group's mean was treated as a variable with experimental error. This would be of minor interest in qualitative studies and might be safely ignored, but might be of considerable importance in quantitative assessments of activity using confidence intervals. When using Bootstrap estimates of standard error and probability plots of the bootstrap samples, the transformed data does not deviate significantly from normality. The standard, bias-corrected percentile limits (BCa), and empirical percentile methods gave very similar results when using resampling statistics to generate the transformed data from groups of n=6. Sample size can be as low as n=4 and still provide useful results. Thus, we have shown that resampling (i.e., bootstrap, Monte Carlo method, computer-intensive methods) can produce the data transform as well as provide confidence intervals using this type of raw data in small groups (n=4 to 6), giving improved statistical analysis of the transformed data (ratio estimates) without accepting a bias from methodology ignoring variation in the control group.

Animals↗

PubMed1990

Genetic counseling in rare syndromes: a resampling method for determining an approximate confidence interval for gene location with linkage data from a single pedigree.

Multipoint linkage analysis is a powerful method for mapping a rare disease gene on the human gene map despite limited genotype and pedigree data. However, there is no standard procedure for determining a confidence interval for gene location by using multipoint linkage analysis. A genetic counselor needs to know the confidence interval for gene location in order to determine the uncertainty of risk estimates provided to a consultant on the basis of DNA studies. We describe a resampling, or "bootstrap," method for deriving an approximate confidence interval for gene location on the basis of data from a single pedigree. This method was used to define an approximate confidence interval for the location of a gene causing nonsyndromal X-linked mental retardation in a single pedigree. The approach seemed robust in that similar confidence intervals were derived by using different resampling protocols. Quantitative bounds for the confidence interval were dependent on the genetic map chosen. Once an approximate confidence interval for gene location was determined for this pedigree, it was possible to use multipoint risk analysis to estimate risk intervals for women of unknown carrier status. Despite the limited genotype data, the combination of the resampling method and multipoint risk analysis had a dramatic impact on the genetic advice available to consultants.

Chromosome Mapping↗

PubMed2000

Bootstrap confidence intervals for relative risk parameters in affected-sib-pair data.

In affected-sib-pair (ASP) studies, parameters such as the locus-specific sibling relative risk, lambda(s), may be estimated and used to decide whether or not to continue the search for susceptibility genes. Typically, a maximum likelihood point estimate of lambda(s) is given, but since this estimate may have substantial variability, it is of interest to obtain confidence limits for the true value of lambda(s). While a variety of methods for doing this exist, there is considerable uncertainty over their reliability. This is because the discrete nature of ASP data and the imposition of genetic "possible triangle" constraints during the likelihood maximization mean that asymptotic results may not apply. In this paper, we use simulation to evaluate the reliability of various asymptotic and simulation-based confidence intervals, the latter being based on a resampling, or bootstrap approach. We seek to identify, from the large pool of methods available, those methods that yield short intervals with accurate coverage probabilities for ASP data. Our results show that many of the most popular bootstrap confidence interval methods perform poorly for ASP data, giving coverage probabilities much lower than claimed. The test-inversion, profile-likelihood, and asymptotic methods, however, perform well, although some care is needed in choice of nuisance parameter. Overall, in simulations under a variety of different genetic hypotheses, we find that the asymptotic methods of confidence interval evaluation are the most reliable, even in small samples. We illustrate our results with a practical application to a real data set, obtaining confidence intervals for the sibling relative risks associated with several loci involved in type 1 diabetes.

Confidence Intervals↗

PubMed1999

Sexual dimorphism in the face of Australopithecus africanus.

Recently discovered crania of Australopithecus africanus from Sterkfontein Member 4 and Makapansgat enlarge the size range of the species and encourage a reappraisal of both the degree and pattern of sexual dimorphism. Resampling methodology (bootstrapping) is used here to establish that A. africanus has a greater craniofacial size range than chimpanzees or modern humans, a range which is best attributed to a moderately high degree of sexual dimorphism. Compared to other fossil hominins, this variation is similar to that of Homo habilis (sensu lato) but less than that of A. boisei. The finding of moderately high dimorphism is corroborated by a CV-based estimate and ratios between those specimens considered to be male and those considered to be female. Inferences about the pattern of craniofacial dimorphism in the A. africanus face currently rely on the relationship of morphology and size. Larger specimens, particularly Stw 505, show prominent superciliary eminences and glabellar regions, but in features related in part to canine size, such as the curvature of the infraorbital surface, large and small specimens of A. africanus are similar. In this respect, the pattern resembles that of modern humans more so than chimpanzees or lowland gorillas. A. africanus may also show novel patterns of sexual dimorphism when compared to extant hominines, such as in the form of the anterior pillar. However, males of the species do not exhibit characteristics of more derived hominins, such as A. robustus.

Animals↗

PubMed1994

DNA-dependent RNA polymerase subunit B as a tool for phylogenetic reconstructions: branching topology of the archaeal domain.

The branching topology of the archaeal (archaebacterial) domain was inferred from sequence comparisons of the largest subunit (B) of DNA-dependent RNA polymerases (RNAP). Both the nucleic acid sequences of the genes coding for RNAP subunit B and the amino acid sequences of the derived gene products were used for phylogenetic reconstructions. Individual analysis of the three nucleotide positions of codons revealed significant inequalities with respect to guanosine and cytosine (GC) content and evolutionary rates. Only the nucleotides at the second codon positions were found to be unbiased by varied GC contents and sufficiently conserved for reliable phylogenetic reconstructions. A decision matrix was used for the combination of the results of distance matrix, maximum parsimony, and maximum likelihood methods. For this purpose the original results (sums of squares, steps, and logarithms of likelihoods) were transformed into comparable effective values and analyzed with methods known from the theory of statistical decisions. Phylogenetic invariants and statistical analysis with resampling techniques (bootstrap and jackknife) confirmed the preferred branching topology, which is significantly different from the topology known from phylogenetic trees based on 16S rRNA sequences. The preferred topology reconstructed by this analysis shows a common stem for the Methanococcales and Methanobacteriales and a separation of the thermophilic sulfur archaea from the methanogens and halophiles. The latter coincides with a unique phylogenetic location of a characteristic splitting event replacing the largest RNAP subunit of thermophilic sulfur archaea by two fragments in methanogens and halophiles. This topology is in good agreement with physiological and structural differences between the various archaea and demonstrates RNAP to be a suitable phylogenetic marker molecule.

Amino Acid Sequence↗

PubMed2005

Molecular evolution and population genetics of circadian clock genes.

This article discusses a number of common methodologies used in the field of population genetics and evolution and reviews their application within circadian rhythm research. We examine the basic principles behind phylogenetic analysis and how these can be used to illuminate clock gene evolution. We then discuss genetic variation between and within species and show how neutrality tests can reveal the signatures of selection or drift on clock genes. These tests are particularly important for moving beyond "just so" stories when discussing the evolution of clock phenotypes, and we provide relevant circadian examples. We also focus on methods that can be used to study genetic variation, such as quantitative trait loci analysis. We discuss the various bootstrapping or resampling techniques that can be applied to generate confidence intervals in the various methodologies and then examine the use of interspecific transformation studies, which can, and have, provide some useful insights, not only into clock gene evolution in particular, but "behavioral" gene evolution in general. Finally, we assess gene/protein alignments and protein structure predictions and their implicit evolutionary bases.

Animals↗

PubMed2006

Dose response explorer: an integrated open-source tool for exploring and modelling radiotherapy dose-volume outcome relationships.

Radiotherapy treatment outcome models are a complicated function of treatment, clinical and biological factors. Our objective is to provide clinicians and scientists with an accurate, flexible and user-friendly software tool to explore radiotherapy outcomes data and build statistical tumour control or normal tissue complications models. The software tool, called the dose response explorer system (DREES), is based on Matlab, and uses a named-field structure array data type. DREES/Matlab in combination with another open-source tool (CERR) provides an environment for analysing treatment outcomes. DREES provides many radiotherapy outcome modelling features, including (1) fitting of analytical normal tissue complication probability (NTCP) and tumour control probability (TCP) models, (2) combined modelling of multiple dose-volume variables (e.g., mean dose, max dose, etc) and clinical factors (age, gender, stage, etc) using multi-term regression modelling, (3) manual or automated selection of logistic or actuarial model variables using bootstrap statistical resampling, (4) estimation of uncertainty in model parameters, (5) performance assessment of univariate and multivariate analyses using Spearman's rank correlation and chi-square statistics, boxplots, nomograms, Kaplan-Meier survival plots, and receiver operating characteristics curves, and (6) graphical capabilities to visualize NTCP or TCP prediction versus selected variable models using various plots. DREES provides clinical researchers with a tool customized for radiotherapy outcome modelling. DREES is freely distributed. We expect to continue developing DREES based on user feedback.

Computer Simulation↗

PubMed2005

Whole-body dosimetry for targeted radionuclide therapy using spectral analysis.

The whole-body dose (WBD) is routinely calculated for targeted radionuclide therapy (TRT). The aim of this work was to investigate the feasibility of using spectral analysis (SA) for the automatic delineation of decay phases, and consequently, the calculation of the WBD given a whole-body (WB) time-activity curve (TAC). SA characterizes the TAC as an arbitrary sum of exponential functions determined by fitting the data with a non-negative least-squares (NNLS) algorithm. The cumulated activity (CA) is calculated analytically as the integral of the fitted curve while the number of phases describing the kinetics of the radiopharmaceutical and the half-lives of the phases can be determined from the spectrum. The uncertainty associated with the estimation of the WBD can be obtained using bootstrap techniques. SA was applied to WB TACs from (186)Re-HEDP and (131)I-mIBG therapies. The results were compared to results obtained using a semiempirical method and showed good agreement in the calculated WBDs. Bootstrapping with resampling on a subset of patients from the two therapies showed much larger coefficient-ofvariation (CV) for the (186)Re-HEDP TACs than for the (131)I-mIBG therapies. We concluded that SA provides a fast, accurate, and reproducible method to obtain WBDs and accurate estimates of the parameters describing the radiotracer kinetics. The method could be extended to other dosimetric applications.

Algorithms↗

PubMed2001

A bootstrapped commingling analysis of platelet monoamine oxidase activity levels corrected for cigarette smoking.

Monoamine oxidase (MAO) activity levels have been suggested as a possible biological marker for alcohol dependence and abuse, as well as for schizophrenia and other psychiatric conditions. Using platelet MAO activities in the Collaborative Study on the Genetics of Alcoholism data set, we applied bootstrapping methods as a novel way to test for admixture in families. This bootstrapping involved resampling in family units and hypothesis testing of the resampled datasets for commingling in the distribution of MAO activity levels. Prior to commingling analysis, we used linear models to find covariates of greatest effect on MAO activity levels. While an alcoholism diagnosis was significant in men (n = 1151, P < 0.0001) and women (n = 1254, P = 0.0003), the effect lost significance after controlling for cigarette smoking, indicating alcoholism and smoking behavior to be highly confounded. When smoking histories were compared, former smokers had levels (mean = 7.1) closer to those who never smoked (mean = 7.0) than to current smokers (mean = 5.4). Furthermore, current daily smoking and time since smoking cessation were significantly related to MAO levels, indicating smoking probably has a direct effect on MAO levels, rather than the reverse. These results suggest that studies using MAO levels as a biological marker should consider smoking as an important covariate. Finally, admixture was found in MAO levels controlled for smoking and sex, possibly indicating a major genetic locus; this confirms previous evidence for admixture.

Biomarkers↗