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Computation of multilocus prior probability of autozygosity for complex inbred pedigrees.

Homozygosity mapping is a very powerful method for mapping rare recessive diseases in humans. In many applications, it is often desirable to compute prior (or unconditional) multilocus probability of autozygosity for inbred pedigrees. This paper proposes a simple yet powerful method for computing the prior multilocus autozygosity probability for complex inbred pedigrees. The method has an added feature of providing explicit multilocus autozygosity probability in terms of recombination fractions, if desired. An example is presented to illustrate the method.

Chromosome Mapping↗

Probabilities of identity-by-descent patterns in sibships when the parents are not genotyped.

An assumption-free algorithm has been applied to compute the probabilities of all possible identity-by-descent (IBD) configurations when the parents have not been genotyped. These probabilities can be used to determine the amount of information that a particular sibship will bring to a nonparametric linkage analysis. It is shown that the number of possible configurations can be extremely large even when the markers are closely spaced and are rather polymorphic. Further, it is not always possible to reduce this number to a manageable one simply by consideration of the relative probabilities of the configurations.

Algorithms↗

The probability of a cancer cluster due to chance alone.

We propose to use a very simple model to test whether a cancer cluster is due to chance alone. We focus on the acute childhood leukaemia cluster in Columbus, Ohio. In 1975, 12 leukaemia cases were observed in Columbus while the expected number is 6 cases per year. According to our simple model, the probability of such an occurrence, due to chance alone, is less than 1 per cent. However, if we divide the child population of the U.S.A. into 200 regions (each region having 200 000 children) then the probability that at least one region will see, in a given year, 12 or more cases is higher than 80 per cent. So in this sense the Columbus cluster could be attributed to chance alone. However, the probability that any of the 200 regions see 18 cases or more in a given year is almost 0. Thus, a cluster of 18 or more cases in a region of 200 000 children should be regarded as highly suspicious and should be investigated.

Acute Disease↗

Prisoner intellectual and personality correlates of offense severity and recidivism probability.

Multiple regression analyses were performed relating the severity of offense and probability of recidivism of 295 prison inmates to their performance on the MMPI and AGCT. The MMPI was found to be correlated with recidivism probability and the recidivism-related component of the Offense Severity variable, while AGCT IQ was found to be correlated with recidivism probability and the non-recidivism-related component of the Offense Severity variable. The implications for future research were discussed regarding this selective sensitivity of the MMPI to recidivism-related variables.

Criminal Psychology↗

Determining the probability of pesticide exposures among migrant farmworkers: results from a feasibility study.

BACKGROUND: Migrant and seasonal farmworkers are exposed to pesticides through their work with crops and livestock. Because workers are usually unaware of the pesticides applied, specific pesticide exposures cannot be determined by interviews. We conducted a study to determine the feasibility of identifying probable pesticide exposures based on work histories. METHODS: The study included 162 farm workers in seven states. Interviewers obtained a lifetime work history including the crops, tasks, months, and locations worked. We investigated the availability of survey data on pesticide use for crops and livestock in the seven pilot states. Probabilities of use for pesticide types (herbicides, insecticides, fungicides, etc.) and specific chemicals were calculated from the available data for two farm workers. The work histories were chosen to illustrate how the quality of the pesticide use information varied across crops, states, and years. RESULTS: For most vegetable and fruit crops there were regional pesticide use data in the late 1970s, no data in the 1980s, and state-specific data every other year in the 1990s. Annual use surveys for cotton and potatoes began in the late 1980s. For a few crops, including asparagus, broccoli, lettuce, strawberries, plums, and Christmas trees, there were no federal data or data from the seven states before the 1990s. CONCLUSIONS: We conclude that identifying probable pesticide exposures is feasible in some locations. However, the lack of pesticide use data before the 1990s for many crops will limit the quality of historic exposure assessment for most workers.

Adolescent↗

Computing conditional recombination probabilities given marker information.

When a parent is homozygous, it is not possible to determine directly whether offspring share an allele identical by descent (IBD) from that parent. However, an IBD probability can be computed using information from linked loci where the parent is heterozygous. To solve this problem for the phase-known case, probability equations and a computer program were developed for efficient computation of conditional probabilities under a Sturt model of chiasma interference. Data are analyzed and contrasted with and without taking interference into account. The effect of failing to account for interference is very small, but the computational cost is also small.

Alleles↗

Sensitivity of prefrontal cortex to changes in target probability: a functional MRI study.

Electrophysiological studies suggest sensitivity of the prefrontal cortex to changes in the probability of an event. The purpose of this study was to determine if subregions of the prefrontal cortex respond differentially to changes in target probabilities using functional magnetic resonance imaging (fMRI). Ten right-handed adults were scanned using a gradient-echo, echo planar imaging sequence during performance of an oddball paradigm. Subjects were instructed to respond to any letter but "X". The frequency of targets (i.e., any letter but X) varied across trials. The results showed that dorsal prefrontal regions were active during infrequent events and ventral prefrontal regions were active during frequent events. Further, we observed an inverse relation between the dorsal and ventral prefrontal regions such that when activity in dorsal prefrontal regions increased, activity in ventral prefrontal regions decreased, and vice versa. This finding may index competing cognitive processes or capacity limitations. Most importantly, these findings taken as a whole suggest that any simple theory of prefrontal cortex function must take into account the sensitivity of this region to changes in target probability.

Adolescent↗

Willingness to pay for reductions in health risks when probabilities are distorted.

We study the willingness to pay for reductions in health risks when people do not evaluate probabilities linearly, as is commonly assumed in elicitations of willingness to pay, but weight probabilities, as is commonly observed in empirical studies of decision under risk. We show that for the levels of baseline risk typically considered, probability weighting strongly affects willingness to pay estimates and may lead to unstable monetary valuations of health.

Europe↗

Improved prediction of fibrosis in chronic hepatitis C using measures of insulin resistance in a probability index.

We sought to develop a clinically useful index comprising standard and physiologically relevant variables to predict the probability of significant hepatic fibrosis in subjects with chronic hepatitis C virus (HCV) infection. Fibrosis was graded as mild (stages F0 or F1) or significant (stages F2-F4). Thirty-five clinical and laboratory parameters were analyzed initially in 176 patients with detectable HCV RNA to derive a fibrosis probability index (FPI) to predict significant fibrosis. This index then was validated in a second group of 126 subjects. Among 18 variables associated with severe fibrosis on univariate analysis, multiple logistic regression analysis identified age, aspartate aminotransferase (AST), total cholesterol level, insulin resistance (by homeostasis model), and past alcohol intake as independent predictors of significant fibrosis. The area under the receiver operating characteristic (ROC) curves was 0.84 for the initial cohort and 0.77 for the validation cohort. In the initial cohort, the sensitivity of the FPI based on these five predictors was 96%, and the negative predictive value was 93% at a score of >/=0.2. At scores >/=0.8, the FPI was 94% specific and had a positive predictive value of 87%. In conclusion, an FPI using routinely assessed markers and incorporating a measure of insulin resistance can reliably predict the probability of significant hepatic fibrosis in most patients with chronic HCV infection. Such an index should prove useful to guide decision making regarding the need for liver biopsy, and potentially for avoiding or deferring biopsy in a large proportion of patients with mild liver disease.

Adult↗

Cells regulate their proliferation through alterations in transition probability.

The proliferation of 3T3, 3T6 and SV3T3 cells was examined by time lapse cinephotography under a number of different growth conditions. It was found that the frequency distributions of intermitotic times of cells with widely different proliferation rates are qualitatively and quantitatively explained by the transition probability model of the cell cycle (Smith and Martin, '73). The behaviour of quiescent cells was characterized by very low values of the transition probability. No "out of cycle" or GO compartment of cells was detectable. From a consideration of these results and those in the literature it appears that the rate of cell proliferation is determined by the value of the "transition probability" (P), and that it is the biochemical manifestation of this parameter that regulates cell growth in vitro and in vivo.

Animals↗

Dual-echo MRI segmentation using vector decomposition and probability techniques: a two-tissue model.

We combined a vector decomposition technique with Gaussian probability thresholding in feature space to segment normal brain tissues, tumors, or other abnormalities on dual-echo MR images. The vector decomposition technique assigns to each voxel a fractional volume for each of two tissues. A probability threshold, based on an assumed Gaussian probability density function describing random noise, isolates a region in feature space for fractional volume calculation that minimizes contamination from other tissues. The calculated fractional volumes are unbiased estimates of the true fractional volumes. The contrast-to-noise ratio (CNR) between tissues on the segmented images is the same as the Euclidean norm of CNRs in the original images. The method is capable of segmenting more than two tissues from a set of dual-echo images by sequentially analyzing different pairs of tissues. The model is analyzed mathematically and in experiments with a phantom. Two clinical examples are presented.

Adenocarcinoma↗

Communicating probability in clinical reports: nurses' numerical associations to verbal expressions.

Verbal estimates of probability (such as likely or certain) commonly used in laboratory, radiological, and clinical reports may be a barrier to effective communication between health care professionals. In this study the investigators sought to determine whether a consensus of numerical meaning existed in a sample of nurses for each of 30 widely used verbal expressions of probability. Seventy female nurses enrolled in a graduate course were surveyed by means of a test-retest procedure using a questionnaire designed to elicit assignments of numerical probability (0% to 100%). The results showed wide inconsistency both between subjects and within subjects.

Communication↗

Protein probabilities in shotgun proteomics: evaluating different estimation methods using a semi-random sampling model.

The calculation of protein probabilities is one of the most intractable problems in large-scale proteomic research. Current available estimating methods, for example, ProteinProphet, PROT_PROBE, Poisson model and two-peptide hits, employ different models trying to resolve this problem. Until now, no efficient method is used for comparative evaluation of the above methods in large-scale datasets. In order to evaluate these various methods, we developed a semi-random sampling model to simulate large-scale proteomic data. In this model, the identified peptides were sampled from the designed proteins and their cross-correlation scores were simulated according to the results from reverse database searching. The simulated result of 18 control proteins was consistent with the experimental one, demonstrating the efficiency of our model. According to the simulated results of human liver sample, ProteinProphet returned slightly higher probabilities and lower specificity than real cases. PROT_PROBE was a more efficient method with higher specificity. Predicted results from a Poisson model roughly coincide with real datasets, and the method of two-peptide hits seems solid but imprecise. However, the probabilities of identified proteins are strongly correlated with several experimental factors including spectra number, database size and protein abundance distribution.

Chromatography, Liquid↗

De novo prediction of polypeptide conformations using dihedral probability grid Monte Carlo methodology.

We tested the dihedral probability grid Monte Carlo (DPG-MC) methodology to determine optimal conformations of polypeptides by applying it to predict the low energy ensemble for two peptides whose solution NMR structures are known: integrin receptor peptide (YGRGDSP, Type II beta-turn) and S3 alpha-helical peptide (YMSEDEL KAAEAAFKRHGPT). DPG-MC involves importance sampling, local random stepping in the vicinity of a current local minima, and Metropolis sampling criteria for acceptance or rejection of new structures. Internal coordinate values are based on side-chain-specific dihedral angle probability distributions (from analysis of high-resolution protein crystal structures). Important features of DPG-MC are: (1) Each DPG-MC step selects the torsion angles (phi, psi, chi) from a discrete grid that are then applied directly to the structure. The torsion angle increments can be taken as S = 60, 30, 15, 10, or 5 degrees, depending on the application. (2) DPG-MC utilizes a temperature-dependent probability function (P) in conjunction with Metropolis sampling to accept or reject new structures. For each peptide, we found close agreement with the known structure for the low energy conformational ensemble located with DPG-MC. This suggests that DPG-MC will be useful for predicting conformations of other polypeptides.

Amino Acid Sequence↗

Estimating the probability of toxicity at the target dose following an up-and-down design.

One of the most important aspects of a phase I trial or other acute toxicity study is estimating accurately the probability of toxicity that is associated with the recommended dose. We use the biased coin up-and-down design to allocate and isotonic regression to estimate toxicity probabilities and determine the recommended dose. We then derive, using bootstrap methods, an estimate of the probability of toxicity at the recommended dose. Small sample properties of this estimator are also evaluated. Published in 2003 by John Wiley & Sons, Ltd.

Bias↗

Sample size for testing and estimating the difference between two paired and unpaired proportions: a 'two-step' procedure combining power and the probability of obtaining a precise estimate.

Clinical trials and scientific research studies are currently planned calculating sample sizes to fulfill power requirements, but the simultaneous need to obtain a satisfactorily precise effect estimate is not widely recognized. I have devised a 'two-step' iterative procedure for comparing two binomial parameters for two paired and unpaired proportions (the most frequent situations in scientific research), which takes into account power and the probability of obtaining a predetermined precision of the effect estimate. The first step provides the sample size for the power of the statistical test, the expected width of its corresponding confidence interval, and the probability of obtaining, under the alternative hypothesis, confidence intervals whose width is less than that expected. The second step iteratively increases this sample size until the probability of obtaining such confidence intervals exceeds a required threshold.

Clinical Trials as Topic↗

Monitoring clinical trials with a conditional probability stopping rule.

Conditional probability procedures offer a flexible means of performing sequential analysis of clinical trials. Since these procedures are not based on repeated significance test, the number and schedule of the interim analyses is less important than with group sequential procedures. Their main disadvantage is that the magnitude of their effect on the significance level is difficult to assess. This paper describes a conditional probability procedure which attempts to maintain the overall significance level by balancing the probabilities of false early rejection and false early acceptance. Monte Carlo sampling results suggest that this procedure can achieve a large reduction in expected sample size without greatly affecting either the significance level or power of the trial.

Binomial Distribution↗

The use of the personalized estimate of death probabilities for medical decision making.

Data coming from the French national statistics on the cause of deaths are used to calculate the probabilities of death from pathologies. These probabilities are calculated according to age, sex, and place of residence of the patient to "personalize" the estimate. This individual prediction of the risk of death is proposed for pathologies for which the feasibility and the utility of prevention measures had been demonstrated. Relative risks of death according to the socioprofessional category, which are coming from the scientific literature, are used to adjust the probabilities of death as a function of the patient socioprofessional category. The aim of this work is to guide a scientist toward a prevention strategy according to the age and characteristics of patient. The use of computers by the scientists will make possible the diffusion of such tool of prediction to improve a personalized prevention.

Cause of Death↗