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Articles 1 - 18 of 18
Full-Text Articles in Physical Sciences and Mathematics
Expert Systems Model For Kentucky Arrow Darter Habitat In The Upper Kentucky River Basin, Benjamin L. Blandford, Michael Shouse
Expert Systems Model For Kentucky Arrow Darter Habitat In The Upper Kentucky River Basin, Benjamin L. Blandford, Michael Shouse
Benjamin L. Blandford
No abstract provided.
Penalized Functional Regression For Next-Generation Sequencing Studies, Olga A. Vsevolozhskaya
Penalized Functional Regression For Next-Generation Sequencing Studies, Olga A. Vsevolozhskaya
Olga A. Vsevolozhskaya
Recent technological advances equipped researchers with capabilities that go beyond traditional genotyping of loci known to be polymorphic in a general population. Genetic sequences of study participants can now be assessed directly. This capability removed technology-driven bias toward scoring predominantly common polymorphisms and let researchers reveal a wealth of rare and sample-specific variants. While the relative contributions of rare and common polymorphisms to trait variation are being debated, researchers are faced with the need for new statistical tools for simultaneous evaluation of all variants within a region. Several research groups demonstrated flexibility and good statistical power of the functional linear …
Estimated Probability Of Becoming A Case Of Drug Dependence In Relation To Duration Of Drug-Taking Experience: A Function Approach, Olga A. Vsevolozhskaya, James C. Anthony
Estimated Probability Of Becoming A Case Of Drug Dependence In Relation To Duration Of Drug-Taking Experience: A Function Approach, Olga A. Vsevolozhskaya, James C. Anthony
Olga A. Vsevolozhskaya
Measured as elapsed time from first use to dependence syndrome onset, the estimated 'induction interval' for cocaine clearly is short relative to the cannabis interval, but little is known about risk of becoming dependent when use persists. Published estimates for this facet of drug dependence epidemiology are from life histories elicited years after first use. To improve estimation, we turn to new data from nationally representative samples of newly incident drug users identified via probability sampling and confidential computer-assisted self-interviews for the National Surveys on Drug Use and Health, 2004-2013. Standardized modules assess first and most recent use, and dependence …
Assessing The Probability That A Finding Is Genuine For Large-Scale Genetic Association Studies, Chia-Ling Kuo, Olga A. Vsevolozhskaya, Dmitri V. Zaykin
Assessing The Probability That A Finding Is Genuine For Large-Scale Genetic Association Studies, Chia-Ling Kuo, Olga A. Vsevolozhskaya, Dmitri V. Zaykin
Olga A. Vsevolozhskaya
Genetic association studies routinely involve massive numbers of statistical tests accompanied by P-values. Whole genome sequencing technologies increased the potential number of tested variants to tens of millions. The more tests are performed, the smaller P-value is required to be deemed significant. However, a small P-value is not equivalent to small chances of a spurious finding and significance thresholds may fail to serve as efficient filters against false results. While the Bayesian approach can provide a direct assessment of the probability that a finding is spurious, its adoption in association studies has been slow, due in part to the ubiquity …
Function-On-Scalar Regression For Genetic Association Studies, Olga A. Vsevolozhskaya, Dmitri V. Zaykin, Qing Lu
Function-On-Scalar Regression For Genetic Association Studies, Olga A. Vsevolozhskaya, Dmitri V. Zaykin, Qing Lu
Olga A. Vsevolozhskaya
We propose a general framework to perform gene/region based analysis of sequencing data by regressing a functional response on one or multiple scalar predictors. Next generation sequencing technologies make it possible to uncover genetic information from millions of variants. Since the observed sequenced variants are very close in their genetic positions, we can consider them to be realizations of random continuous functions. Therefore, instead of analyzing multiple individual genetic variants per subject, we can estimate the underlying continuous function and treat it as a functional response in a regression model. Smoothing splines are used to fit these functional responses by …
Functional Analysis Of Variance For Association Studies, Olga A. Vsevolozhskaya, Dmitri V. Zaykin, Mark C. Greenwood, Changshuai Wei, Qing Lu
Functional Analysis Of Variance For Association Studies, Olga A. Vsevolozhskaya, Dmitri V. Zaykin, Mark C. Greenwood, Changshuai Wei, Qing Lu
Olga A. Vsevolozhskaya
While progress has been made in identifying common genetic variants associated with human diseases, for most of common complex diseases, the identified genetic variants only account for a small proportion of heritability. Challenges remain in finding additional unknown genetic variants predisposing to complex diseases. With the advance in next-generation sequencing technologies, sequencing studies have become commonplace in genetic research. The ongoing exome-sequencing and whole-genome-sequencing studies generate a massive amount of sequencing variants and allow researchers to comprehensively investigate their role in human diseases. The discovery of new disease-associated variants can be enhanced by utilizing powerful and computationally efficient statistical methods. …
Penalized Functional Regression For Next-Generation Sequencing Studies, Olga A. Vsevolozhskaya
Penalized Functional Regression For Next-Generation Sequencing Studies, Olga A. Vsevolozhskaya
Olga A. Vsevolozhskaya
Advances in next-generation sequencing (NGS) technologies make it possible to examining nearly every variant on the human genome. Because of the high density of variants, genotypes within a genetic region can be thought of as a finite sample realization of some underlying stochastic process. The aim of vast majority of NSG studies is to explore an association between a set of genetic variants and qualitative/quantitative traits. To address this aim, we propose a general framework based on functional dependent variable and univariate covariates. We fit our model using penalized least squares criterion. We note that within this framework, the spline …
From Drug Use To Dependence: A Multiparametric Approach, Olga A. Vsevolozhskaya, James C. Anthony
From Drug Use To Dependence: A Multiparametric Approach, Olga A. Vsevolozhskaya, James C. Anthony
Olga A. Vsevolozhskaya
One of the hallmarks of a drug dependence (DD) process is an escalation in rate of drug self-administration (DSA). We seek to extend current biostatistical approaches for epidemiological research on drug dependence processes via an investigation of a four-parameter dose-effect curve (DEC).
Confidence Interval Estimation In R-Das: State-Level Estimates For Extra-Medical Use Of Prescription Pain Relievers, Olga A. Vsevolozhskaya, James C. Anthony
Confidence Interval Estimation In R-Das: State-Level Estimates For Extra-Medical Use Of Prescription Pain Relievers, Olga A. Vsevolozhskaya, James C. Anthony
Olga A. Vsevolozhskaya
The specific methodological aims of our research are: 1) to clarify statistical inference procedures used by R-DAS to produce confidence interval estimates; 2) to review a simple solution to some of the research questions not currently addressed by R-DAS (i.e., with respect to tests of significance); and 3) to describe how in certain situations the percentages and the corresponding standard errors, which are suppressed from the R-DAS output due to the confidentiality concerns can be estimated “by hand”.
Pairwise Comparison Of Treatment Levels In Functional Analysis Of Variance With Application To Erythrocyte Hemolysis, Olga A. Vsevolozhskaya, Mark C. Greenwood, Dmitri Holodov
Pairwise Comparison Of Treatment Levels In Functional Analysis Of Variance With Application To Erythrocyte Hemolysis, Olga A. Vsevolozhskaya, Mark C. Greenwood, Dmitri Holodov
Olga A. Vsevolozhskaya
Motivated by a practical need for the comparison of hemolysis curves at various treatment levels, we propose a novel method for pairwise comparison of mean functional responses. The hemolysis curves—the percent hemolysis as a function of time—of mice erythrocytes (red blood cells) by hydrochloric acid have been measured among different treatment levels. This data set fits well within the functional data analysis paradigm, in which a time series is considered as a realization of the underlying stochastic process or a smooth curve. Previous research has only provided methods for identifying some differences in mean curves at different times. We propose …
Combining Functions And The Closure Principle For Performing Follow-Up Tests In Functional Analysis Of Variance, Olga A. Vsevolozhskaya, Mark C. Greenwood, G. J. Bellante, S. L. Powell, R. L. Lawrence, K. S. Repasky
Combining Functions And The Closure Principle For Performing Follow-Up Tests In Functional Analysis Of Variance, Olga A. Vsevolozhskaya, Mark C. Greenwood, G. J. Bellante, S. L. Powell, R. L. Lawrence, K. S. Repasky
Olga A. Vsevolozhskaya
Functional analysis of variance involves testing for differences in functional means across kk groups in nn functional responses. If a significant overall difference in the mean curves is detected, one may want to identify the location of these differences. Cox and Lee (2008) proposed performing a point-wise test and applying the Westfall–Young multiple comparison correction. We propose an alternative procedure for identifying regions of significant difference in the functional domain. Our procedure is based on a region-wise test and application of a combining function along with the closure multiplicity adjustment principle. We give an explicit formulation of how to implement …
Use Of P-Values To Evaluate The Probability Of A Genuine Finding In Large-Scale Genetic Association Studies, Olga A. Vsevolozhskaya, Qing Lu, Chia-Ling Kuo, Dmitri V. Zaykin
Use Of P-Values To Evaluate The Probability Of A Genuine Finding In Large-Scale Genetic Association Studies, Olga A. Vsevolozhskaya, Qing Lu, Chia-Ling Kuo, Dmitri V. Zaykin
Olga A. Vsevolozhskaya
To claim the existence of an association in modern genome-wide association studies (GWAS), a nominal P-value has to exceed a stringent Bonferroni-adjusted significance level. Despite strictness of the correction, a significant P-value does not indicate high probability that the claimed association is genuine. A simple Bayesian solution -- the False Positive Report Probability (FPRP) -- was previously proposed to convert the observed P-value to the corresponding probability of no true association. Although the FPRP solution is highly popular, it does not reflect probability that a particular finding is false. Here, we offer a simple POFIG method -- a Probability that …
Association Studies For Sequencing Data With Functional Analysis Of Variance, Olga A. Vsevolozhskaya, Mark C. Greenwood, Changshuai Wei, Qing Lu
Association Studies For Sequencing Data With Functional Analysis Of Variance, Olga A. Vsevolozhskaya, Mark C. Greenwood, Changshuai Wei, Qing Lu
Olga A. Vsevolozhskaya
The rapid development of next generation sequencing technologies and accompanying reduction in cost produce an increasing number of single nucleotide polymorphisms (SNPs) that can be identified across the genome. Analyzing high-dimensional genomic data is a challenge and requires development of new statistical methods. We propose to use the functional analysis of variance (FANOVA) to perform inference for sequencing data. FANOVA is used to test for differences in functional means of k groups over time. We suggest using FANOVA to test for a significant difference among SNPs between levels of a phenotype, such as the presence or absence of a disease. …
Excel Tips And Tricks Handout, Julene L. Jones
Excel Tips And Tricks Handout, Julene L. Jones
Julene L. Jones
Handout given at UK Libraries' Third Thursday: "Excel tips and tricks"
Resampling-Based Multiple Comparison Procedure With Application To Point-Wise Testing With Functional Data, Olga A. Vsevolozhskaya, Mark C. Greenwood
Resampling-Based Multiple Comparison Procedure With Application To Point-Wise Testing With Functional Data, Olga A. Vsevolozhskaya, Mark C. Greenwood
Olga A. Vsevolozhskaya
No abstract provided.
A Proposed Methodology For Pairwise Comparison Of Treatment Levels In A Functional Data Setting, Olga A. Vsevolozhskaya, Mark C. Greenwood, Dmitri B. Holodov
A Proposed Methodology For Pairwise Comparison Of Treatment Levels In A Functional Data Setting, Olga A. Vsevolozhskaya, Mark C. Greenwood, Dmitri B. Holodov
Olga A. Vsevolozhskaya
An effect of procaine (novocaine) on the structural and functional properties of somatic cell membranes was studied based on erythrocyte acidity resistance. To study the effect of different levels of procaine (novocaine) in the bloodstream, the dynamics of the red blood cells rupture was measured after the addition of hydrochloric acid to the red blood cell suspension. The measurements were taken every 15 seconds for 12 minutes. Since the response was sampled at a high frequency, it can be regarded as functional data. One of the research questions was to compare rates of hemolysis under different procaine (novocaine) dosages. We …
A Proposed Methodology For Performing Follow-Up Tests To Compare Pairs Of Treatment Levels In Functional Linear Models, Olga A. Vsevolozhskaya, Mark C. Greenwood, Dmitri B. Holodov
A Proposed Methodology For Performing Follow-Up Tests To Compare Pairs Of Treatment Levels In Functional Linear Models, Olga A. Vsevolozhskaya, Mark C. Greenwood, Dmitri B. Holodov
Olga A. Vsevolozhskaya
No abstract provided.
Follow-Up Testing In Functional Anova, Olga A. Vsevolozhskaya, Mark C. Greenwood
Follow-Up Testing In Functional Anova, Olga A. Vsevolozhskaya, Mark C. Greenwood
Olga A. Vsevolozhskaya
Functional analysis of variance involves testing for differences in functional means across k groups in n functional responses. If a significant overall difference in the mean curves is detected, one may want to identify the location of these differences. Two different follow-up testing methods are discussed and contrasted. A point-wise test proposed by Cox and Lee (2008) is compared to a test based on regions of the functional domain. The methods are contrasted in terms of weak control of the family-wise error rate, strong control of the family-wise error rate, and power.