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PubMedDate not supplied

[Different anxiety levels in rats selected for their ability to acquire the conditioned reflex of active avoidance].

Experiments were carried out in rat strains selected for high (KHA) and low (KLA) rates of active avoidance conditioning in a shuttle box. The elevated plus-maze was used for anxiety measurements. Naive KHA rats, as compared with KLA ones, demonstrated much higher anxiety scores. Inescapable electric footshock had opposite effects on anxiety levels in KHA and KLA rats, i.e., it increased anxiety scores in KLA rats and decreased in KHA. The results point to the role of anxiety in adaptive behaviour, e.g., in learning abilities.

Animals↗
PubMed1994

A combined test of linkage heterogeneity.

This paper focuses on the problem of testing for heterogeneity once linkage is established. In an investigation of genetic linkage, Morton first proposed a general purpose test to detect heterogeneity in the recombination fraction. Two more commonly used tests of linkage heterogeneity are the admixture test (A-test) of Smith, Ott, and Risch and Baron, and the B-test of Risch. All are likelihood-ratio tests, but they differ in the models specifying the heterogeneity. A new test of heterogeneity in the presence of linkage is presented here. I propose a mixture model of heterogeneity, which allows the recombination fraction to vary among families, as does the B-model, yet also allows some families to be unlinked, as the A-model does. This model contains the A and B models as special cases and thus allows a direct test (D-test), which can provide justification for choosing one of these extremes.

Family↗
PubMed1994

Analysis of polymorphic variation in drug metabolism: I. Kernal density estimation.

Kernel density estimation was examined as an objective, nonparametric approach to the detection of polymorphic variation in distributions containing multiple complex data sets. Power curves were constructed for the kernel density estimate based on its ability to detect worked bimodality in stimulated distributions as a function of the distribution size, the fraction contained within a particular subdistribution, and the location of the mean of that subdistribution with respect to the mean of the overall distribution. Comparisons were then made between kernel density estimation and the Kolmogorov-Smirnov test of maximal differences. Results showed that kernel density estimation performed as well or better than the Kolmogorov-Smirnov test and offered a number of advantages, including identification of the frequency and placement of individual modes and antimodes. The Kolmogorov-Smirnov test, on the other hand, examined normality of a distribution rather than modality or inherent polymorphism, and the outcome was highly dependent on the subdistribution location and total distribution size. We conclude that kernel density estimation is an excellent method for analysis of polymorphic variation in drug metabolism.

Genetic Variation↗
PubMed1996

Association of factor VII:C levels with environmental and genetic factors in patients with ischaemic heart disease and coronary atheroma characterised by angiography.

Elevated Factor VII:C (FVII:C) levels are an independent risk factor for acute myocardial infarction. To examine the association between FVII:C levels, genetic and environmental factors in patients with a history suggestive of ischaemic heart disease, 270 patients were studied. FVII:C levels were significantly associated with the Msp I and promoter insertion polymorphisms. FVII:C correlated with environmental factors, and these correlations remained when analysed by genotype. In a multiple regression model, genotype, body mass index, cholesterol, triglycerides and gender remained as independent and significant predictors of FVII:C levels. There was no significant difference in FVII:C concentrations with severity of atheroma, or in patients with a history of myocardial infarction. These findings provide further evidence linking FVII:C with Msp I and promoter insertion genotypes and with environmental factors in established IHD, but suggest there is not a genotype-environment interaction or a relationship between FVII:C levels and severity of ischaemic heart disease.

Aged↗
PubMed1977

Segregation analysis of thalassemia in Ferrara.

Segregation analysis of 996 families in which the gene for beta-thalassemia was segregating showed no distortion of expected Mendelian ratios. No appreciable frequency of sporadic cases was detected. It was suggested that segregation distortion is not a mechanism which contributes to the maintenance of polymorphism in the beta-thalassemia system in the population of the Ferrara area.

Computers↗
PubMed1998

Selection, convergence, and intragenic recombination in HLA diversity.

To account for high degrees of human leukocyte antigen (HLA) diversity, a method is proposed for detecting intragenic recombination or gene conversion separately from parallel substitutions or convergent evolution. An application of the method to HLA protein sequences suggests that intragenic recombination played important roles in HLA-B and DPB1, some in HLA-A and DRB1, and least in HLA-C and DQB1 diversity. However, the extent of diversity of these molecules does not necessarily correlate with the frequency of intragenic recombination, supporting the view that (balancing) selection is a primary agent of HLA diversity and often leads to convergent evolution. Computer simulation is carried out to examine two models of balancing selection under the coupled effect with mutation, intragenic recombination, and random drift in a diploid population. It is emphasized that break points by intragenic recombination need be specified to account for HLA diversity. Implications of HLA diversity in human evolution are briefly discussed.

Amino Acid Sequence↗
PubMed1985

Variance components analysis of forced expiration in families.

Familial aggregation of forced expiration (as measured by forced expiratory volume in 1 sec (FEV1) and the ratio of this to total forced vital capacity (FEV1/FVC) was analyzed in 439 adult members of 108 families ascertained through control patients who had participated in a genetic and epidemiologic study of chronic obstructive pulmonary disease. Residual values for both FEV1 and FEV1/FVC obtained from regression on age, sex, race, and cigarette smoking (and height for FEV1) were used in a variance components analysis to assess the relative importance of genetic and nongenetic factors influencing familial aggregation of pulmonary function among adults. For both residual FEV1 and residual FEV1/FVC, the "best" model among a series of genetic and nongenetic models was a simple additive genetic model. A modified score test, which is robust to the assumption of multivariate normality, was used to test the significance of these estimated components. Under the most parsimonious model, additive genetic variation accounted for 28% of the variation in residual FEV1 in 108 families and 24% of the variation in residual FEV1/FVC. After outlying individuals were identified by examining goodness-of-fit statistics, the simple genetic model still gave the best fit to these data. There was little indication of non-normality in FEV1 in these families; however, FEV1/FVC did show evidence of non-normality when examining goodness-of-fit statistics. This genetic component contributing to the distribution of forced expiration may be a factor in the familial aggregation of certain respiratory diseases.

Adult↗
PubMed2006

Non-linear tests for identifying differentially expressed genes or genetic networks.

MOTIVATION: One of the recently developed statistics for identifying differentially expressed genetic networks is Hotelling T2 statistic, which is a quadratic form of difference in linear functions of means of gene expressions between two types of tissue samples, and so their power is limited. RESULTS: To improve the power of test statistics, a general statistical framework for construction of non-linear tests is presented, and two specific non-linear test statistics that use non-linear transformations of means are developed. Asymptotical distributions of the non-linear test statistics under the null and alternative hypothesis are derived. It has been proved that under some conditions the power of the non-linear test statistics is higher than that of the T2 statistic. Besides theory, to evaluate in practice the performance of the non-linear test statistics, they are applied to two real datasets. The preliminary results demonstrate that the P-values of the non-linear statistics for testing differential expressions of the genetic networks are much smaller than those of the T2 statistic. And furthermore simulations show the Type I errors of the non-linear statistics agree with the threshold used and the statistics fit the chi2 distribution. SUPPLEMENTARY INFORMATION: Supplementary data are available on Bioinformatics online.

Algorithms↗
PubMed2004

From micro- to macroevolution through quantitative genetic variation: positive evidence from field crickets.

Quantitative genetics has been introduced to evolutionary biologists with the suggestion that microevolution could be directly linked to macroevolutionary patterns using, among other parameters, the additive genetic variance/ covariance matrix (G) which is a statistical representation of genetic constraints to evolution. However, little is known concerning the rate and pattern of evolution of G in nature, and it is uncertain whether the constraining effect of G is important over evolutionary time scales. To address these issues, seven species of field crickets from the genera Gryllus and Teleogryllus were reared in the laboratory, and quantitative genetic parameters for morphological traits were estimated from each of them using a nested full-sibling family design. We used three statistical approaches (T method, Flury hierarchy, and Mantel test) to compare G matrices or genetic correlation matrices in a phylogenetic framework. Results showed that G matrices were generally similar across species, with occasional differences between some species. We suggest that G has evolved at a low rate, a conclusion strengthened by the consideration that part of the observed across-species variation in G can be explained by the effect of a genotype by environment interaction. The observed pattern of G matrix variation between species could not be predicted by either morphological trait values or phylogeny. The constraint hypothesis was tested by comparing the multivariate orientation of the reconstructed ancestral G matrix to the orientation of the across-species divergence matrix (D matrix, based on mean trait values). The D matrix mainly revealed divergence in size and, to a much smaller extent, in a shape component related to the ovipositor length. This pattern of species divergence was found to be predictable from the ancestral G matrix in agreement with the expectation of the constraint hypothesis. Overall, these results suggest that the G matrix seems to have an influence on species divergence, and that macroevolution can be predicted, at least qualitatively, from quantitative genetic theory. Alternative explanations are discussed.

Analysis of Variance↗
PubMed1989

[A novel method for determining an integrated character in quantitative genetics].

This paper describes a novel method using maximum entropy principle introduced by Shannon to construct a unique integrated character and gives a comparison between this method and multivariate statistics in quantitative genetics. In multivariate genetic analysis multivariate statistics is usually used for a polygenic system of multiple quantitative traits to form several complex character. Genetic analysis can be implemented through treating these correlated elementary traits by using the technique of principal component analysis or canonical correlation. Differing from the multivariate statistics, this paper presents a new method using maximum-entropy principle to obtain a unique integrated character from a set of correlated quantitative traits. This method has the advantages of simple mathematical structure and process, simple and clear results.

Animals↗
PubMed2006

Statistical modeling of biomedical corpora: mining the Caenorhabditis Genetic Center Bibliography for genes related to life span.

BACKGROUND: The statistical modeling of biomedical corpora could yield integrated, coarse-to-fine views of biological phenomena that complement discoveries made from analysis of molecular sequence and profiling data. Here, the potential of such modeling is demonstrated by examining the 5,225 free-text items in the Caenorhabditis Genetic Center (CGC) Bibliography using techniques from statistical information retrieval. Items in the CGC biomedical text corpus were modeled using the Latent Dirichlet Allocation (LDA) model. LDA is a hierarchical Bayesian model which represents a document as a random mixture over latent topics; each topic is characterized by a distribution over words. RESULTS: An LDA model estimated from CGC items had better predictive performance than two standard models (unigram and mixture of unigrams) trained using the same data. To illustrate the practical utility of LDA models of biomedical corpora, a trained CGC LDA model was used for a retrospective study of nematode genes known to be associated with life span modification. Corpus-, document-, and word-level LDA parameters were combined with terms from the Gene Ontology to enhance the explanatory value of the CGC LDA model, and to suggest additional candidates for age-related genes. A novel, pairwise document similarity measure based on the posterior distribution on the topic simplex was formulated and used to search the CGC database for "homologs" of a "query" document discussing the life span-modifying clk-2 gene. Inspection of these document homologs enabled and facilitated the production of hypotheses about the function and role of clk-2. CONCLUSION: Like other graphical models for genetic, genomic and other types of biological data, LDA provides a method for extracting unanticipated insights and generating predictions amenable to subsequent experimental validation.

Animals↗
PubMed2006

Farm Scale Evaluations of spring-sown genetically modified herbicide-tolerant crops: a statistical assessment.

Primary results from the Farm Scale Evaluations (FSEs) of spring-sown genetically modified herbicide-tolerant crops were published in 2003. We provide a statistical assessment of the results for count data, addressing issues of sample size (n), efficiency, power, statistical significance, variability and model selection. Treatment effects were consistent between rare and abundant species. Coefficients of variation averaged 73% but varied widely. High variability in vegetation indicators was usually offset by large n and treatment effects, whilst invertebrate indicators often had smaller n and lower variability; overall, achieved power was broadly consistent across indicators. Inferences about treatment effects were robust to model misspecification, justifying the statistical model adopted. As expected, increases in n would improve detectability of effects whilst, for example, halving n would have resulted in a loss of significant results of about the same order. 40% of the 531 published analyses had greater than 80% power to detect a 1.5-fold effect; reducing n by one-third would most likely halve the number of analyses meeting this criterion. Overall, the data collected vindicated the initial statistical power analysis and the planned replication. The FSEs provide a valuable database of variability and estimates of power under various sample size scenarios to aid planning of more efficient future studies.

Agriculture↗
PubMed2001

Triangle test statistic in discordant sib pairs: test of genetic heterogeneity of asthma and atopy in CSGA families.

The purpose of our study was to detect genetic heterogeneity (i.e., different genotype relative risks of genetic factor) between atopic and non-atopic asthma and between atopy associated or independent of asthma. Genetic heterogeneity was tested in the Caucasian Collaborative Study on the Genetics of Asthma families using the TTS (triangle test statistic) and the predivided sample test. The TTS was proposed to detect both linkage and intra-sib-pair genetic heterogeneity; such heterogeneity may exist if the sibs differ for a factor on which the penetrances of the putative linked gene depend. The TTS has been applied to asthmatic pairs discordant for atopy and atopic sib pairs discordant for asthma. To confirm genetic heterogeneity detected by the TTS, the predivided sample test was also applied among concordant and discordant sib pairs. The analyses detected a genetic factor on chromosome 8p that could be involved in atopy with different genotype relative risks according to whether asthma is present. This would suggest a pleiotropic effect of this genetic factor in asthma and atopy. Two other regions located on chromosomes 8q and 20p were detected for genetic heterogeneity with asthma and atopy, respectively, but the factor of heterogeneity could be independent from the presence of atopy or asthma, respectively. It could be a characteristic of the disease such as the severity or the presence of an environmental factor.

Adult↗
PubMed2004

Detecting phylogenetic incongruence using BIONJ: an improvement of the ILD test.

The problem of testing for congruence between phylogenetic data has long been debated among phylogeneticists, but reaches a critical point with the availability of large amount of biological sequences. Notably in prokaryotes, where the amount of lateral transfers is believed to be important, the inference of phylogenies using multiple genes requires testing for incongruence before concatenating the genes. On another scale, incongruence tests can be used to detect recombination points within single gene alignments. The incongruence length difference test (ILD), based on parsimony, has been proved to be useful for finding incongruent data sets, but its application remains limited to small data sets for computational time reasons. Here, we have adapted the principle of ILD to the BIONJ algorithm. This algorithm is based on a tree length minimisation criterion and is suitable to replace parsimony in this test when used with uncorrected distance (model-free approach). We show that this new test, ILD-BIONJ, while being much faster, is often more accurate than the ILD test, especially when the alignments compared are simulated under different evolutionary models.

Algorithms↗
PubMed2004

[The genetic revolution-impact on therapy and prevention].

After the successful sequencing of the human genome the genetic variation between individuals will be worked out in the near future. The genetic differences are the basis for different predispositions to diseases. The next goal is to correlate the host of genetic variants with phenotypes. This endeavor has already been successful for monogenic diseases; however, it will also be possible in genetically complex diseases. If a trait follows a monogenic mode of inheritance, a phenotype results nearly completely from a single mutation; in genetically complex diseases there exists only a statistical relationship. Predictive genetic diagnostics should only be considered after genetic counseling; it makes sense, if there exists efficient prevention or therapy, respectively. This applies e. g. to various familial cancer predispositions. In the future, medical doctors should be able to apply genetic risk figures and to convey them to their patients.

Genetic Counseling↗