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Articles 601 - 630 of 776
Full-Text Articles in Genetics and Genomics
Structural Characterization Of Human Uch37, E. S. Burgie, C. Bingman, Ameet Soni, G. N. Phillips Jr.
Structural Characterization Of Human Uch37, E. S. Burgie, C. Bingman, Ameet Soni, G. N. Phillips Jr.
Computer Science Faculty Works
Uch37 is a de-ubiquitylating enzyme that is functionally linked with the 26S proteasome via Rpn13, and is essential for metazoan development. Here, we report the X-ray crystal structure of full-length human Uch37 at 2.95 Å resolution. Uch37's catalytic domain is similar to those of all UCH enzymes characterized to date. The C-terminal extension is elongated, predominantly helical and contains coiled coil interactions. Additionally, we provide an initial characterization of Uch37's oligomeric state and identify a systematic error in previous analyses of Uch37 activity. Taken together, these data provide a strong foundation for further analysis of Uch37's several functions.
Probabilistic Ensembles For Improved Inference In Protein-Structure Determination, Ameet Soni, J. Shavlik
Probabilistic Ensembles For Improved Inference In Protein-Structure Determination, Ameet Soni, J. Shavlik
Computer Science Faculty Works
Protein X-ray crystallography — the most popular method for determining protein structures — remains a laborious process requiring a great deal of manual crystallographer effort to interpret low-quality protein images. Automating this process is critical in creating a high-throughput protein-structure determination pipeline. Previously, our group developed ACMI, a probabilistic framework for producing protein-structure models from electron-density maps produced via X-ray crystallography. ACMI uses a Markov Random Field to model the three-dimensional (3D) location of each non-hydrogen atom in a protein. Calculating the best structure in this model is intractable, so ACMI uses approximate inference methods to estimate the optimal structure. …
Successful Genotyping Of Microsatellites In The Woolly Mammoth, Yasuko Ishida, Alfred L. Roca, Stephen Fratpietro, Alex D. Greenwood
Successful Genotyping Of Microsatellites In The Woolly Mammoth, Yasuko Ishida, Alfred L. Roca, Stephen Fratpietro, Alex D. Greenwood
Biological Sciences Faculty Publications
Genetic analyses using ancient DNA from Pleistocene and early Holocene fossils have largely relied on mitochondrial DNA (mtDNA) sequences. Among woolly mammoths, Mammuthus primigenius, mtDNA analyses have identified 2 distinct clades (I and II) that diverged 1-2 Ma. Here, we establish that microsatellite markers can be effective on Pleistocene samples, successfully genotyping woolly mammoth specimens at 2 loci. Although significant differentiation at the 2 microsatellite loci was not detected between 16 clade I and 4 clade II woolly mammoths, our results demonstrate that the nuclear population structure of Pleistocene species can be examined using fast-evolving nuclear microsatellite markers.
Functional Promiscuity Of The Cog0720 Family, Gabriela Phillips, Laura L. Grochowski, Shilah Bonnett, Huimin Xu, Marc Bailly, Crysten Haas-Blaby, Basma El Yacoubi, Dirk Iwata-Reuyl, Robert H. White, Valérie De Crécy-Lagard
Functional Promiscuity Of The Cog0720 Family, Gabriela Phillips, Laura L. Grochowski, Shilah Bonnett, Huimin Xu, Marc Bailly, Crysten Haas-Blaby, Basma El Yacoubi, Dirk Iwata-Reuyl, Robert H. White, Valérie De Crécy-Lagard
Chemistry Faculty Publications and Presentations
The biosynthesis of GTP derived metabolites such as tetrahydrofolate (THF), biopterin (BH4), and the modified tRNA nucleosides queuosine (Q) and archaeosine (G+) relies on several enzymes of the Tunnel-fold superfamily. A subset of these proteins include the 6-pyruvoyl-tetrahydropterin (PTPS-II), PTPS-III, and PTPS-I homologs, all members of the COG0720 family, that have been previously shown to transform 7,8-dihydroneopterin triphosphate (H2NTP) into different products. PTPS-II catalyzes the formation of 6-pyruvoyltetrahydropterin in the BH4 pathway. PTPS-III catalyzes the formation of 6-hydroxylmethyl-7,8-dihydropterin in the THF pathway. PTPS-I catalyzes the formation of 6-carboxy-5,6,7,8-tetrahydropterin in the Q pathway. Genes of these …
Effects Of Ions On The Activity Of Peptidyl-Trna Hydrolase, Blake Holloway
Effects Of Ions On The Activity Of Peptidyl-Trna Hydrolase, Blake Holloway
Summer Community of Scholars Posters (RCEU and HCR Combined Programs)
No abstract provided.
Development And Application Of Methods Used To Source Prehistoric Southwestern Maize: A Review, Larry Benson
Development And Application Of Methods Used To Source Prehistoric Southwestern Maize: A Review, Larry Benson
United States Geological Survey: Staff Publications
Archaeological cobs free of mineral contaminants should be used to source the soils in which they were grown. Mineral contaminants often contain much higher concentrations of metals than vegetal materials and can alter a cob’s apparent metal and heavy-isotope content. Cleaning a cob via immersion in an acid solution for more than a few minutes will result in the incongruent and sometimes complete leaching of metals, including strontium (Sr), from the cob. When using 87Sr/86Sr to determine the location of potential agriculture fields, it is best to either integrate several depth-integrated soil samples or to integrate several …
On The Global Stability Of A Generalized Cholera Epidemiological Model, Yuanji Cheng, Jin Wang, Xiuxiang Yang
On The Global Stability Of A Generalized Cholera Epidemiological Model, Yuanji Cheng, Jin Wang, Xiuxiang Yang
Mathematics & Statistics Faculty Publications
In this paper, we conduct a careful global stability analysis for a generalized cholera epidemiological model originally proposed in [J. Wang and S. Liao, A generalized cholera model and epidemic/endemic analysis, J. Biol. Dyn. 6 (2012), pp. 568-589]. Cholera is a water-and food-borne infectious disease whose dynamics are complicated by the multiple interactions between the human host, the pathogen, and the environment. Using the geometric approach, we rigorously prove the endemic global stability for the cholera model in three-dimensional (when the pathogen component is a scalar) and four-dimensional (when the pathogen component is a vector) systems. This work unifies the …
A Study Of Correlations Between The Definition And Application Of The Gene Ontology, Yuji Mo
A Study Of Correlations Between The Definition And Application Of The Gene Ontology, Yuji Mo
Department of Computer Electronics and Engineering: Dissertations, Theses, and Student Research
When using the Gene Ontology (GO), nucleotide and amino acid sequences are annotated by terms in a structured and controlled vocabulary organized into relational graphs. The usage of the vocabulary (GO terms) in the annotation of these sequences may diverge from the relations defined in the ontology. We measure the consistency of the use of GO terms by comparing GO's defined structure to the terms' application. To do this, we first use synthetic data with different characteristics to understand how these characteristics influence the correlation values determined by various similarity measures. Using these results as a baseline, we found that …
Assessing The Impact Of Non-Differential Genotyping Errors On Rare Variant Tests Of Association, Scott Powers, Shyam Gopalakrishnan, Nathan L. Tintle
Assessing The Impact Of Non-Differential Genotyping Errors On Rare Variant Tests Of Association, Scott Powers, Shyam Gopalakrishnan, Nathan L. Tintle
Faculty Work Comprehensive List
Background/Aims: We aim to quantify the effect of non-differential genotyping errors on the power of rare variant tests and identify those situations when genotyping errors are most harmful. Methods: We simulated genotype and phenotype data for a range of sample sizes, minor allele frequencies, disease relative risks and numbers of rare variants. Genotype errors were then simulated using five different error models covering a wide range of error rates. Results: Even at very low error rates, misclassifying a common homozygote as a heterozygote translates into a substantial loss of power, a result that is exacerbated even further as the minor …
Estimation Of A Non-Parametric Variable Importance Measure Of A Continuous Exposure, Chambaz Antoine, Pierre Neuvial, Mark J. Van Der Laan
Estimation Of A Non-Parametric Variable Importance Measure Of A Continuous Exposure, Chambaz Antoine, Pierre Neuvial, Mark J. Van Der Laan
U.C. Berkeley Division of Biostatistics Working Paper Series
We define a new measure of variable importance of an exposure on a continuous outcome, accounting for potential confounders. The exposure features a reference level x0 with positive mass and a continuum of other levels. For the purpose of estimating it, we fully develop the semi-parametric estimation methodology called targeted minimum loss estimation methodology (TMLE) [van der Laan & Rubin, 2006; van der Laan & Rose, 2011]. We cover the whole spectrum of its theoretical study (convergence of the iterative procedure which is at the core of the TMLE methodology; consistency and asymptotic normality of the estimator), practical implementation, simulation …
Multiple Testing Of Local Maxima For Detection Of Peaks In Chip-Seq Data, Armin Schwartzman, Andrew Jaffe, Yulia Gavrilov, Clifford A. Meyer
Multiple Testing Of Local Maxima For Detection Of Peaks In Chip-Seq Data, Armin Schwartzman, Andrew Jaffe, Yulia Gavrilov, Clifford A. Meyer
Harvard University Biostatistics Working Paper Series
No abstract provided.
Gene By Bmi Interactions Influencing C-Reactive Protein Levels In European-Americans, Sarah Tudor
Gene By Bmi Interactions Influencing C-Reactive Protein Levels In European-Americans, Sarah Tudor
Dissertations and Theses (Open Access)
C-Reactive Protein (CRP) is a biomarker indicating tissue damage, inflammation, and infection. High-sensitivity CRP (hsCRP) is an emerging biomarker often used to estimate an individual’s risk for future coronary heart disease (CHD). hsCRP levels falling below 1.00 mg/l indicate a low risk for developing CHD, levels ranging between 1.00 mg/l and 3.00 mg/l indicate an elevated risk, and levels exceeding 3.00 mg/l indicate high risk. Multiple Genome-Wide Association Studies (GWAS) have identified a number of genetic polymorphisms which influence CRP levels. SNPs implicated in such studies have been found in or near genes of interest including: CRP, APOE, APOC, IL-6, …
A Unified Approach To Non-Negative Matrix Factorization And Probabilistic Latent Semantic Indexing, Karthik Devarajan, Guoli Wang, Nader Ebrahimi
A Unified Approach To Non-Negative Matrix Factorization And Probabilistic Latent Semantic Indexing, Karthik Devarajan, Guoli Wang, Nader Ebrahimi
COBRA Preprint Series
Non-negative matrix factorization (NMF) by the multiplicative updates algorithm is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into two matrices, W and H, each with nonnegative entries, V ~ WH. NMF has been shown to have a unique parts-based, sparse representation of the data. The nonnegativity constraints in NMF allow only additive combinations of the data which enables it to learn parts that have distinct physical representations in reality. In the last few years, NMF has been successfully applied in a variety of areas such as natural language processing, information retrieval, image processing, speech recognition …
Stability Analysis And Application Of A Mathematical Cholera Model, Shu Liao, Jim Wang
Stability Analysis And Application Of A Mathematical Cholera Model, Shu Liao, Jim Wang
Mathematics & Statistics Faculty Publications
In this paper, we conduct a dynamical analysis of the deterministic cholera model proposed in [9]. We study the stability of both the disease-free and endemic equilibria so as to explore the complex epidemic and endemic dynamics of the disease. We demonstrate a real-world application of this model by investigating the recent cholera outbreak in Zimbabwe. Meanwhile, we present numerical simulation results to verify the analytical predictions.
A Bayesian Model Averaging Approach For Observational Gene Expression Studies, Xi Kathy Zhou, Fei Liu, Andrew J. Dannenberg
A Bayesian Model Averaging Approach For Observational Gene Expression Studies, Xi Kathy Zhou, Fei Liu, Andrew J. Dannenberg
COBRA Preprint Series
Identifying differentially expressed (DE) genes associated with a sample characteristic is the primary objective of many microarray studies. As more and more studies are carried out with observational rather than well controlled experimental samples, it becomes important to evaluate and properly control the impact of sample heterogeneity on DE gene finding. Typical methods for identifying DE genes require ranking all the genes according to a pre-selected statistic based on a single model for two or more group comparisons, with or without adjustment for other covariates. Such single model approaches unavoidably result in model misspecification, which can lead to increased error …
Component Extraction Of Complex Biomedical Signal And Performance Analysis Based On Different Algorithm, Hemant Pasusangai Kasturiwale
Component Extraction Of Complex Biomedical Signal And Performance Analysis Based On Different Algorithm, Hemant Pasusangai Kasturiwale
Johns Hopkins University, Dept. of Biostatistics Working Papers
Biomedical signals can arise from one or many sources including heart ,brains and endocrine systems. Multiple sources poses challenge to researchers which may have contaminated with artifacts and noise. The Biomedical time series signal are like electroencephalogram(EEG),electrocardiogram(ECG),etc The morphology of the cardiac signal is very important in most of diagnostics based on the ECG. The diagnosis of patient is based on visual observation of recorded ECG,EEG,etc, may not be accurate. To achieve better understanding , PCA (Principal Component Analysis) and ICA algorithms helps in analyzing ECG signals . The immense scope in the field of biomedical-signal processing Independent Component Analysis( …
Preliminary Analysis Of An Agent-Based Model For A Tick-Borne Disease, Holly Gaff
Preliminary Analysis Of An Agent-Based Model For A Tick-Borne Disease, Holly Gaff
Biological Sciences Faculty Publications
Ticks have a unique life history including a distinct set of life stages and a single blood meal per life stage. This makes tick-host interactions more complex from a mathematical perspective. In addition, any model of these interactions must involve a significant degree of stochasticity on the individual tick level. In an attempt to quantify these relationships, I have developed an individual-based model of the interactions between ticks and their hosts as well as the transmission of tick-borne disease between the two populations. The results from this model are compared with those from previously published differential equation based population models. …
Isolation By Distance Explains Genetic Structure Of Buggy Creek Virus, A Bird-Associated Arbovirus, Abinash Padhi, Amy T. Moore, Mary Bomberger Brown, Jerome E. Foster, Martin Pfeffer, Charles R. Brown
Isolation By Distance Explains Genetic Structure Of Buggy Creek Virus, A Bird-Associated Arbovirus, Abinash Padhi, Amy T. Moore, Mary Bomberger Brown, Jerome E. Foster, Martin Pfeffer, Charles R. Brown
School of Natural Resources: Faculty Publications
Many of the arthropod-borne viruses (arboviruses) show extensive genetic variability and are widely distributed over large geographic areas. Understanding how virus genetic structure varies in space may yield insight into how these pathogens are adapted to and dispersed by different hosts or vectors, the relative importance of mutation, drift, or selection in generating genetic variability, and where and when epidemics or epizootics are most likely to occur. However, because most arboviruses tend to be sampled opportunistically and often cannot be isolated in large numbers at a given locale, surprisingly little is known about their spatial genetic structure on the local …
A Generalized Approach For Testing The Association Of A Set Of Predictors With An Outcome: A Gene Based Test, Benjamin A. Goldstein, Alan E. Hubbard, Lisa F. Barcellos
A Generalized Approach For Testing The Association Of A Set Of Predictors With An Outcome: A Gene Based Test, Benjamin A. Goldstein, Alan E. Hubbard, Lisa F. Barcellos
U.C. Berkeley Division of Biostatistics Working Paper Series
In many analyses, one has data on one level but desires to draw inference on another level. For example, in genetic association studies, one observes units of DNA referred to as SNPs, but wants to determine whether genes that are comprised of SNPs are associated with disease. While there are some available approaches for addressing this issue, they usually involve making parametric assumptions and are not easily generalizable. A statistical test is proposed for testing the association of a set of variables with an outcome of interest. No assumptions are made about the functional form relating the variables to the …
Inflated Type I Error Rates When Using Aggregation Methods To Analyze Rare Variants In The 1000 Genomes Project Exon Sequencing Data In Unrelated Individuals: Summary Results From Group 7 At Genetic Analysis Workshop 17, Nathan L. Tintle, Hugues Aschard, Inchi Hu, Nora Nock, Haitian Wang, Elizabeth Pugh
Inflated Type I Error Rates When Using Aggregation Methods To Analyze Rare Variants In The 1000 Genomes Project Exon Sequencing Data In Unrelated Individuals: Summary Results From Group 7 At Genetic Analysis Workshop 17, Nathan L. Tintle, Hugues Aschard, Inchi Hu, Nora Nock, Haitian Wang, Elizabeth Pugh
Faculty Work Comprehensive List
As part of Genetic Analysis Workshop 17 (GAW17), our group considered the application of novel and standard approaches to the analysis of genotype-phenotype association in next-generation sequencing data. Our group identified a major issue in the analysis of the GAW17 next-generation sequencing data: type I error and false-positive report probability rates higher than those expected based on empirical type I error levels (as high as 90%). Two main causes emerged: population stratification and long-range correlation (gametic phase disequilibrium) between rare variants. Population stratification was expected because of the diverse sample. Correlation between rare variants was attributable to both random causes …
Identification Of Genetic Association Of Multiple Rare Variants Using Collapsing Methods, Yan V. Sun, Yun Ju Sung, Nathan L. Tintle, Andreas Ziegler
Identification Of Genetic Association Of Multiple Rare Variants Using Collapsing Methods, Yan V. Sun, Yun Ju Sung, Nathan L. Tintle, Andreas Ziegler
Faculty Work Comprehensive List
Next-generation sequencing technology allows investigation of both common and rare variants in humans. Exomes are sequenced on the population level or in families to further study the genetics of human diseases. Genetic Analysis Workshop 17 (GAW17) provided exomic data from the 1000 Genomes Project and simulated phenotypes. These data enabled evaluations of existing and newly developed statistical methods for rare variant sequence analysis for which standard statistical methods fail because of the rareness of the alleles. Various alternative approaches have been proposed that overcome the rareness problem by combining multiple rare variants within a gene. These approaches are termed collapsing …
Analysis Of Biological Features Associated With Meiotic Recombination Hot And Cold Spots In Saccharomyces Cerevisiae, Loren Hansen, Nak-Kyeong Kim, Leonardo Mariño-Ramírez, David Landsman
Analysis Of Biological Features Associated With Meiotic Recombination Hot And Cold Spots In Saccharomyces Cerevisiae, Loren Hansen, Nak-Kyeong Kim, Leonardo Mariño-Ramírez, David Landsman
Mathematics & Statistics Faculty Publications
Meiotic recombination is not distributed uniformly throughout the genome. There are regions of high and low recombination rates called hot and cold spots, respectively. The recombination rate parallels the frequency of DNA double-strand breaks (DSBs) that initiate meiotic recombination. The aim is to identify biological features associated with DSB frequency. We constructed vectors representing various chromatin and sequence-based features for 1179 DSB hot spots and 1028 DSB cold spots. Using a feature selection approach, we have identified five features that distinguish hot from cold spots in Saccharomyces cerevisiae with high accuracy, namely the histone marks H3K4me3, H3K14ac, H3K36me3, and H3K79me3; …
A Parallel Graph Sampling Algorithm For Analyzing Gene Correlation Networks, Kathryn Dempsey Cooper, Kanimathi Duraisamy, Hesham Ali, Sanjukta Bhowmick
A Parallel Graph Sampling Algorithm For Analyzing Gene Correlation Networks, Kathryn Dempsey Cooper, Kanimathi Duraisamy, Hesham Ali, Sanjukta Bhowmick
Interdisciplinary Informatics Faculty Publications
Effcient analysis of complex networks is often a challenging task due to its large size and the noise inherent in the system. One popular method of overcoming this problem is through graph sampling, that is extracting a representative subgraph from the larger network. The accuracy of the sample is validated by comparing the combinatorial properties of the subgraph and the original network. However, there has been little study in comparing networks based on the applications that they represent. Furthermore, sampling methods are generally applied agnostically, without mapping to the requirements of the underlying analysis. In this paper,we introduce a parallel …
Weighted Scores Method For Regression Models With Dependent Data, Aristidis K. Nikoloulopoulos, Harry Joe, N. Rao Chaganty
Weighted Scores Method For Regression Models With Dependent Data, Aristidis K. Nikoloulopoulos, Harry Joe, N. Rao Chaganty
Mathematics & Statistics Faculty Publications
There are copula-based statistical models in the literature for regression with dependent data such as clustered and longitudinal overdispersed counts, for which parameter estimation and inference are straightforward. For situations where the main interest is in the regression and other univariate parameters and not the dependence, we propose a "weighted scores method", which is based on weighting score functions of the univariate margins. The weight matrices are obtained initially fitting a discretized multivariate normal distribution, which admits a wide range of dependence. The general methodology is applied to negative binomial regression models. Asymptotic and small-sample efficiency calculations show that our …
Evaluation Of Essential Genes In Correlation Networks Using Measures Of Centrality, Kathryn Dempsey Cooper, Hesham Ali
Evaluation Of Essential Genes In Correlation Networks Using Measures Of Centrality, Kathryn Dempsey Cooper, Hesham Ali
Interdisciplinary Informatics Faculty Proceedings & Presentations
Correlation networks are emerging as powerful tools for modeling relationships in high-throughput data such as gene expression. Other types of biological networks, such as protein-protein interaction networks, are popular targets of study in network theory, and previous analysis has revealed that network structures identified using graph theoretic techniques often relate to certain biological functions. Structures such as highly connected nodes and groups of nodes have been found to correspond to essential genes and protein complexes, respectively. The correlation network, which measures the level of co-variation of gene expression levels, shares some structural properties with other types of biological networks. We …
A Novel Correlation Networks Approach For The Identification Of Gene Targets, Kathryn Dempsey Cooper, Stephen Bonasera, Dhundy Raj Bastola, Hesham Ali
A Novel Correlation Networks Approach For The Identification Of Gene Targets, Kathryn Dempsey Cooper, Stephen Bonasera, Dhundy Raj Bastola, Hesham Ali
Interdisciplinary Informatics Faculty Proceedings & Presentations
Correlation networks are emerging as a powerful tool for modeling temporal mechanisms within the cell. Particularly useful in examining coexpression within microarray data, studies have determined that correlation networks follow a power law degree distribution and thus manifest properties such as the existence of “hub” nodes and semicliques that potentially correspond to critical cellular structures. Difficulty lies in filtering coincidental relationships from causative structures in these large, noise-heavy networks. As such, computational expenses and algorithm availability limit accurate comparison, making it difficult to identify changes between networks. In this vein, we present our work identifying temporal relationships from microarray data …
Evaluating Methods For The Analysis Of Rare Variants In Sequence Data, Alexander Luedtke, Scott Powers, Ashley Petersen, Alexandra Sitarik, Airat Bekmetjev, Nathan L. Tintle
Evaluating Methods For The Analysis Of Rare Variants In Sequence Data, Alexander Luedtke, Scott Powers, Ashley Petersen, Alexandra Sitarik, Airat Bekmetjev, Nathan L. Tintle
Faculty Work Comprehensive List
A number of rare variant statistical methods have been proposed for analysis of the impending wave of next-generation sequencing data. To date, there are few direct comparisons of these methods on real sequence data. Furthermore, there is a strong need for practical advice on the proper analytic strategies for rare variant analysis. We compare four recently proposed rare variant methods (combined multivariate and collapsing, weighted sum, proportion regression, and cumulative minor allele test) on simulated phenotype and next-generation sequencing data as part of Genetic Analysis Workshop 17. Overall, we find that all analyzed methods have serious practical limitations on identifying …
Evaluating Methods For Combining Rare Variant Data In Pathway-Based Tests Of Genetic Association, Ashley Petersen, Alexandra Sitarik, Alexander Luedtke, Scott Powers, Airat Bekmetjev, Nathan L. Tintle
Evaluating Methods For Combining Rare Variant Data In Pathway-Based Tests Of Genetic Association, Ashley Petersen, Alexandra Sitarik, Alexander Luedtke, Scott Powers, Airat Bekmetjev, Nathan L. Tintle
Faculty Work Comprehensive List
Analyzing sets of genes in genome-wide association studies is a relatively new approach that aims to capitalize on biological knowledge about the interactions of genes in biological pathways. This approach, called pathway analysis or gene set analysis, has not yet been applied to the analysis of rare variants. Applying pathway analysis to rare variants offers two competing approaches. In the first approach rare variant statistics are used to generate p-values for each gene (e.g., combined multivariate collapsing [CMC] or weighted-sum [WS]) and the gene-level p-values are combined using standard pathway analysis methods (e.g., gene set enrichment analysis or …
Identifying Rare Variants From Exome Scans: The Gaw17 Experience, Saurabh Ghosh, Heike Bickeboller, Julia Bailey, Joan E. Bailey-Wilson, Rita Cantor, Robert Culverhouse, Warwick Daw, Anita L. Destefano, Corinne D. Engelman, Anthony Hinrichs, Jeanine Houwing-Duistermaat, Inke R. Konig, Jack Kent, Nan Laird, Nathan Pankratz, Andrew Paterson, Elizabeth Pugh, Brian Suarez, Yan Sun, Alun Thomas, Nathan L. Tintle, Xiaofeng Zhu, Andreas Ziegler, Jean W. Maccluer, Laura Almasy
Identifying Rare Variants From Exome Scans: The Gaw17 Experience, Saurabh Ghosh, Heike Bickeboller, Julia Bailey, Joan E. Bailey-Wilson, Rita Cantor, Robert Culverhouse, Warwick Daw, Anita L. Destefano, Corinne D. Engelman, Anthony Hinrichs, Jeanine Houwing-Duistermaat, Inke R. Konig, Jack Kent, Nan Laird, Nathan Pankratz, Andrew Paterson, Elizabeth Pugh, Brian Suarez, Yan Sun, Alun Thomas, Nathan L. Tintle, Xiaofeng Zhu, Andreas Ziegler, Jean W. Maccluer, Laura Almasy
Faculty Work Comprehensive List
Genetic Analysis Workshop 17 (GAW17) provided a platform for evaluating existing statistical genetic methods and for developing novel methods to analyze rare variants that modulate complex traits. In this article, we present an overview of the 1000 Genomes Project exome data and simulated phenotype data that were distributed to GAW17 participants for analyses, the different issues addressed by the participants, and the process of preparation of manuscripts resulting from the discussions during the workshop
Analysis Of The Genetic Structure Of Bithynia Tentaculata Snail Populations In Wisconsin And Minnesota, Sarah J. Whalen
Analysis Of The Genetic Structure Of Bithynia Tentaculata Snail Populations In Wisconsin And Minnesota, Sarah J. Whalen
All Graduate Theses, Dissertations, and Other Capstone Projects
In recent years, there have been tens of thousands of waterfowl mortalities in Wisconsin and Minnesota. An invasive species of snail, Bithynia tentaculata, is a host for the trematode parasites (Cyathocotyle bushiensis and Sphaeridiotrema globulus) that have caused these deaths. A microsatellite-enriched genomic library was detected using DNA from a B. tentaculata specimen from Lake Onalaska (Pool 7 of the Upper Mississippi River). Seven polymorphic microsatellite loci were used to genotype snails collected from Lake Butte des Morts, Shawano Lake, and Lake Onalaska in Wisconsin, as well as Lake Winnibigoshish in Minnesota. The genetic diversity of each population was measured …