Genetics and Genomics Commons^™

Causal Effect Estimation In Sequencing Studies: A Bayesian Method To Account For Confounder Adjustment Uncertainty, Chi Wang, Jinpeng Liu, David W. Fardo

Biostatistics Faculty Publications

Estimating the causal effect of a single nucleotide variant (SNV) on clinical phenotypes is of interest in many genetic studies. The effect estimation may be confounded by other SNVs as a result of linkage disequilibrium as well as demographic and clinical characteristics. Because a large number of these other variables, which we call potential confounders, are collected, it is challenging to select and adjust for the variables that truly confound the causal effect. The Bayesian adjustment for confounding (BAC) method has been proposed as a general method to estimate the average causal effect in the presence of a large number …

General Equations For Natural Selection Under Complete Dominance, Kasthuri Kannan, Adriana Heguy

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Exploring The Space Of Rna Secondary Structures, Heather C. Smith

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

User-Centered Design Of Multi-Gene Sequencing Panel Reports For Clinicians., Elizabeth Cutting, Meghan Banchero, Amber L Beitelshees, James J Cimino, Guilherme Del Fiol, Ayse P Gurses, Mark A Hoffman, Linda Jo Bone Jeng, Kensaku Kawamoto, Mark Kelemen, Harold Alan Pincus, Alan R Shuldiner, Marc S Williams, Toni I Pollin, Casey Lynnette Overby

Manuscripts, Articles, Book Chapters and Other Papers

The objective of this study was to develop a high-fidelity prototype for delivering multi-gene sequencing panel (GS) reports to clinicians that simulates the user experience of a final application. The delivery and use of GS reports can occur within complex and high-paced healthcare environments. We employ a user-centered software design approach in a focus group setting in order to facilitate gathering rich contextual information from a diverse group of stakeholders potentially impacted by the delivery of GS reports relevant to two precision medicine programs at the University of Maryland Medical Center. Responses from focus group sessions were transcribed, coded and …

Metabolic Profiling And Polymer Formation Of Gene Silenced Potato Periderms, Qing Cai

Dissertations, Theses, and Capstone Projects

Suberin is a biopolyester constituent of specialized plant periderm tissues formed within the phellem cell walls. Suberin and waxes of the periderm layer act to prevent water diffusion, mechanical breakdown and pathogenic invasion in plants. Ferulic esters, ω-hydroxyacids and α,ω-fatty diacids are considered to be the most important linkage between aliphatic and aromatic suberin domains and also linked with cell-wall polysaccharides. The potato gene FHT (fatty ω- hydroxyacid/fatty alcohol hydroxycinnamoyl transferase) esterifies ferulic acid to suberin. Diminished levels of feruloyl transferase activity have been associated with lowered amounts of feruloyl esters of fatty acids in both suberin-associated waxes and suberin …

Weighted-Samgsr: Combining Significance Analysis Of Microarray-Gene Set Reduction Algorithm With Pathway Topology-Based Weights To Select Relevant Genes, Suyan Tian, Howard H. Chang, Chi Wang

Biostatistics Faculty Publications

Background: It has been demonstrated that a pathway-based feature selection method that incorporates biological information within pathways during the process of feature selection usually outperforms a gene-based feature selection algorithm in terms of predictive accuracy and stability. Significance analysis of microarray-gene set reduction algorithm (SAMGSR), an extension to a gene set analysis method with further reduction of the selected pathways to their respective core subsets, can be regarded as a pathway-based feature selection method.

Methods: In SAMGSR, whether a gene is selected is mainly determined by its expression difference between the phenotypes, and partially by the number of pathways to …

Identification Of Control Targets In Boolean Molecular Network Models Via Computational Algebra, David Murrugarra, Alan Veliz-Cuba, Boris Aguilar, Reinhard Laubenbacher

Mathematics Faculty Publications

Background: Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type …

Methods To Account For Breed Composition In A Bayesian Gwas Method Which Utilizes Haplotype Clusters, Danielle F. Wilson-Wells

Department of Statistics: Dissertations, Theses, and Student Research

In livestock, prediction of an animal’s genetic merit using genomic information is becoming increasingly common. The models used to make these predictions typically assume that we are sampling from a homogeneous population. However, in both commercial and experimental populations the sire and dam of an individual may be a mixture of different breeds. Haplotype models can capture this population structure.

Two models based on breed specific haplotype clusters where developed to account for differences across multiple breeds. The first model utilizes the breed composition of the individual, while the second utilizes the breed composition from the sire and dam. Haplotype …

Incremental Phylogenetics By Repeated Insertions: An Evolutionary Tree Algorithm, Peter Revesz, Zhiqiang Li

School of Computing: Faculty Publications

We introduce the idea of constructing hypothetical evolutionary trees using an incremental algorithm that inserts species one-by-one into the current evolutionary tree. The method of incremental phylogenetics by repeated insertions lead to an algorithm that can be used on DNA, RNA and amino acid sequences. According to experimental results on both synthetic and biological data, the new algorithm generates more accurate evolutionary trees than the UPGMA and the Neighbor Joining algorithms.

Diversity, Structure And Convergent Evolution Of The Global Sponge Microbiome, Torsten Thomas, Lucas Moitinho-Silva, Miguel Lurgi, Johannes R. Bjork, Cole Easson, Carmen Astudillo-Garcia, Julie B. Olson, Patrick M. Erwin, Susanna Lopez-Legentil, Heidi Luter, Andia Chaves Fonnegra, Rodrigo Costa, Peter J. Schupp, Laura Steindler, Dirk Erpenbeck, Jack Gilbert, Rob Knight, Gail Ackermann, Jose V. Lopez, Michael W. Taylor, Robert W. Thacker, Jose M. Montoya, Ute Hentschel, Nicole S. Webster

Marine & Environmental Sciences Faculty Articles

Sponges (phylum Porifera) are early-diverging metazoa renowned for establishing complex microbial symbioses. Here we present a global Porifera microbiome survey, set out to establish the ecological and evolutionary drivers of these host–microbe interactions.We show that sponges are a reservoir of exceptional microbial diversity and major contributors to the total microbial diversity of the world’s oceans. Little commonality in species composition or structure is evident across the phylum, although symbiont communities are characterized by specialists and generalists rather than opportunists. Core sponge microbiomes are stable and characterized by generalist symbionts exhibiting amensal and/or commensal interactions. Symbionts that are phylogenetically unique to …

Characterization Of The Marine Sponge Amphimedon Compressa Microbiome Across A Spatial Gradient, Renee Michelle Potens

HCNSO Student Theses and Dissertations

Diverse and ecologically important microbial communities (microbiomes) are symbiotic within marine sponges. In this study, the microbiome of Amphimedon compressa from three sample locations (Broward and Dade Counties, Southeast Florida, USA and the Southern Caribbean, Bocas del Toro, Panama) is characterized using 16S rRNA Illumina sequencing. The predominant taxa are Proteobacteria and Cyanobacteria, as expected for Low Microbial Abundance sponges, accounting for over 53% of the total microbiome community. The numbers of Operational Taxonomic Units (OTUs) decrease from Broward County (2,900) to Dade County (2,300) and then Bocas del Toro (1,200). The correlates to a decreasing north-south gradient of …

The Foundations Of Network Dynamics In An Rna Recombinase System, Jessica Anne Mellor Yeates

Dissertations and Theses

How life originated from physical and chemical processes is one of the great questions still unanswered today. Studies towards this effort have transitioned from the notion of a single self-replicating entity to the idea that a network of interacting molecules made this initial biological leap. In order to understand the chemical kinetic and thermodynamic mechanisms that could engender pre-life type networks we present an empirical characterization of a network of RNA recombinase molecules. We begin with 1-, 2-, and 3-molecular ensembles and provide a game theoretic analysis to describe the frequency dependent dynamics of competing and cooperating RNA genotypes. This …

Graph Mining For Next Generation Sequencing: Leveraging The Assembly Graph For Biological Insights, Julia Warnke-Sommer, Hesham Ali

Computer Science Faculty Publications

Background: The assembly of Next Generation Sequencing (NGS) reads remains a challenging task. This is especially true for the assembly of metagenomics data that originate from environmental samples potentially containing hundreds to thousands of unique species. The principle objective of current assembly tools is to assemble NGS reads into contiguous stretches of sequence called contigs while maximizing for both accuracy and contig length. The end goal of this process is to produce longer contigs with the major focus being on assembly only. Sequence read assembly is an aggregative process, during which read overlap relationship information is lost as reads are …

Identification Of Biomarkers For The Overall Survival Of Ovarian Cancer Patients, Kristi Mai

Graduate Theses and Dissertations

Rapid advance in sequencing technology has led to genome-wide analysis of genetic and epigenetic features simultaneously, making it possible to understand the biological mechanisms underlying cancer initiation and progression. However, how to identify important prognostic features poses a great challenge for both statistical modeling and computing. In this thesis, a network-based approach is applied to the Cancer Genome Atlas (TCGA) ovarian cancer data to identify important genes related to the overall survival of ovarian cancer patients. In the first step, a stepwise correlation-based selector is used to reduce the dimensionality of TCGA data, by filtering out a large number of …

Global Genetic Connectivity And Diversity In A Shark Of High Conservation Concern, The Oceanic Whitetip, Carcharhinus Longimanus, Cassandra L. Ruck

HCNSO Student Theses and Dissertations

The oceanic whitetip shark, Carcharhinus longimanus, is a circumtropical pelagic shark of high conservation concern (IUCN Red List: “Critically Endangered” in the Western North and Western Central Atlantic and “Vulnerable” globally). I present the first, population genetic assessment of the oceanic whitetip shark on a global scale, based on analysis of two mitochondrial genome regions (entire 1066-1067 bp control region and 784 bp partial ND4 gene), and nine nuclear microsatellite loci. No population structure was detected within the Western Atlantic. However, highly significant population structure was detected between Western Atlantic and Indo-Pacific Ocean sharks across all markers. Additionally, a …

Scalable Parallelization Of A Markov Coalescent Genealogy Sampler, Philip E. Davis

Masters Theses

Coalescent genealogy samplers are effective tools for the study of population genetics. They are used to estimate the historical parameters of a population based upon the sampling of present-day genetic information. A popular approach employs Markov chain Monte Carlo (MCMC) methods. While effective, these methods are very computationally intensive, often taking weeks to run. Although attempts have been made to leverage parallelism in an effort to reduce runtimes, they have not resulted in scalable solutions. Due to the inherently sequential nature of MCMC methods, their performance has suffered diminishing returns when applied to large-scale computing clusters. In the interests of …

Conditional Screening For Ultra-High Dimensional Covariates With Survival Outcomes, Hyokyoung Grace Hong, Jian Kang, Yi Li

The University of Michigan Department of Biostatistics Working Paper Series

Identifying important biomarkers that are predictive for cancer patients' prognosis is key in gaining better insights into the biological influences on the disease and has become a critical component of precision medicine. The emergence of large-scale biomedical survival studies, which typically involve excessive number of biomarkers, has brought high demand in designing efficient screening tools for selecting predictive biomarkers. The vast amount of biomarkers defies any existing variable selection methods via regularization. The recently developed variable screening methods, though powerful in many practical setting, fail to incorporate prior information on the importance of each biomarker and are less powerful in …

Bottom-Up Ggm Algorithm For Constructing Multilayered Hierarchical Gene Regulatory Networks That Govern Biological Pathways Or Processes, Sapna Kupari, Wenping Deng, Chathura J. Gunasekara, Vincent Chiang, Huann-Sheng Chen, Hairong Wei, Et. Al.

Michigan Tech Publications, Part 1

Background: Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways.

Results: A bottom-up graphic Gaussian model (GGM) algorithm was developed for constructing ML-hGRN operating above a biological pathway using small- to medium-sized microarray or RNA-seq data sets. The algorithm first placed genes of a pathway at the bottom layer and began to construct an ML-hGRN by evaluating all combined triple genes: two pathway genes and one regulatory gene. The algorithm retained all triple genes where a regulatory …

A Mitochondrial Dna-Based Computational Model Of The Spread Of Human Populations, Peter Revesz

School of Computing: Faculty Publications

This paper presents a mitochondrial DNA-based computational model of the spread of human populations. The computation model is based on a new measure of the relatedness of two populations that may be both heterogeneous in terms of their set of mtDNA haplogroups. The measure gives an exponentially increasing weight for the similarity of two haplogroups with the number of levels shared in the mtDNA classification tree. In an experiment, the computational model is applied to the study of the relatedness of seven human populations ranging from the Neolithic through the Bronze Age to the present. The human populations included in …

Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang

COBRA Preprint Series

Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …

Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret

UW Biostatistics Working Paper Series

We have frequently implemented crossover studies to evaluate new therapeutic interventions for genital herpes simplex virus infection. The outcome measured to assess the efficacy of interventions on herpes disease severity is the viral shedding rate, defined as the frequency of detection of HSV on the genital skin and mucosa. We performed a simulation study to ascertain whether our standard model, which we have used previously, was appropriately considering all the necessary features of the shedding data to provide correct inference. We simulated shedding data under our standard, validated assumptions and assessed the ability of 5 different models to reproduce the …

Enscat: Clustering Of Categorical Data Via Ensembling, Bertrand S. Clarke, Saeid Amiri, Jennifer L. Clarke

Department of Statistics: Faculty Publications

Background: Clustering is a widely used collection of unsupervised learning techniques for identifying natural classes within a data set. It is often used in bioinformatics to infer population substructure. Genomic data are often categorical and high dimensional, e.g., long sequences of nucleotides. This makes inference challenging: The distance metric is often not well-defined on categorical data; running time for computations using high dimensional data can be considerable; and the Curse of Dimensionality often impedes the interpretation of the results. Up to the present, however, the literature and software addressing clustering for categorical data has not yet led to a standard …

Importance Of Hereditary And Selected Environmental Risk Factors In The Etiology Of Inflammatory Breast Cancer: A Case-Comparison Study., Roxana Moslehi, Elizabeth Freedman, Nur Zeinomar, Carmela Veneroso, Paul H. Levine

Epidemiology Faculty Publications

BACKGROUND: To assess the importance of heredity in the etiology of inflammatory breast cancer (IBC), we compared IBC patients to several carefully chosen comparison groups with respect to the prevalence of first-degree family history of breast cancer.

METHODS: IBC cases (n = 141) were compared to non-inflammatory breast cancer cases (n = 178) ascertained through George Washington University (GWU) with respect to the prevalence of first-degree family history of breast cancer and selected environmental/lifestyle risk factors for breast cancer. Similar comparisons were conducted with subjects from three case-control studies: breast cancer cases (n = 1145) and unaffected controls (n = …

Identification Of Lead-Sensitive Expression And Splicing Quantitative Trait Loci In Drosophila Melanogaster By Analysis Of Rna-Seq Data, Wen Qu

Wayne State University Dissertations

Lead exposure has long been one of the most important topics in global public health since it is a potent developmental neurotoxin. Here, we conducted an expression QTL (eQTLs) analysis, which is genome-wide association analysis of genetic variants with differential gene expression, in the male heads of 79 Drosophila melanogaster recombinant inbred lines originally from eight parental strains in the presence or absence of developmental exposure to 250 µM lead acetate. The aim was to study the effects of lead exposure on gene expression and identify the lead-responsive genes. After detecting 1,536 cis-eQTLs and 952 trans-eQTLs (1000 permutation threshold at …

An Alignment-Free "Metapeptide" Strategy For Metaproteomic Characterization Of Microbiome Samples Using Shotgun Metagenomic Sequencing, Damon H. May, Emma Timmins-Schiffman, Molly P. Mikan, H. Rodger Harvey, Elhanan Borenstein, Brook L. Nunn, William S. Noble

OES Faculty Publications

In principle, tandem mass spectrometry can be used to detect and quantify the peptides present in a microbiome sample, enabling functional and taxonomic insight into microbiome metabolic activity. However, the phylogenetic diversity constituting a particular microbiome is often unknown, and many of the organisms present may not have assembled genomes. In ocean microbiome samples, with particularly diverse and uncultured bacterial communities, it is difficult to construct protein databases that contain the bulk of the peptides in the sample without losing detection sensitivity due to the overwhelming number of candidate peptides for each tandem mass spectrum. We describe a method for …

Vanadium Toxicological Potential Versus Its Pharmacological Activity: New Developments And Research, Agnieszka Ścibior, Juan Llopis, Alvin A. Holder, Mario Altamirano-Lozano

Chemistry & Biochemistry Faculty Publications

Scibior, A., Llopis, J., Holder, A. A., & Altamirano-Lozano, M. (2016). Vanadium toxicological potential versus its pharmacological activity: New developments and research. Oxidative Medicine and Cellular Longevity, 2016, 1-2. doi: 10.1155/2016/7612347

Sample Size Estimation For Genomics Experiments With Dependent End Points, Desmond Koomson

Open Access Theses & Dissertations

In typical genomics studies involving numerous association tests of gene mutations with a disease, error rate control via multiplicity adjustment is paramount because even if all genes were to be non-differentially associated, we would still make some false positives. Many methods exist that incorporate the control of multiplicity for normally distributed endpoints in sample size estimation, but none addresses the issue for non-normally correlated endpoints.

One common practice in the literature is to assume an equal correlation among all differentially associated or expressed genes, thereby using the generalized binomial or beta-binomial model to compute the comparison-wise power of detecting these …

Ecology Of Two Reintroduced Black Bear Populations In The Central Appalachians, Sean Mccarthy Murphy

Theses and Dissertations--Animal and Food Sciences

Reintroduced populations are vulnerable to demographic and environmental stochasticity, deleterious genetic effects, and reduced population fitness, all of which can increase extinction probability. Population viability is principle to determining the status of reintroduced populations and for guiding management decisions. To attempt to reestablish black bear (Ursus americanus) populations in the central Appalachians, two reintroductions using small founder groups occurred during the 1990s in the Big South Fork area along the Kentucky-Tennessee border (BSF) and in the Jefferson National Forest along the Kentucky-Virginia border (KVP). My objectives were to estimate demographic and genetic parameters, and to evaluate long-term viability …

Resolving Gnetum Evolutionary History, Angela Mcfadden

All Master's Theses

Gnetum are non-flowering seed plants of the tropics, indigenous to South America, Africa, and Asia. This group of about 40 species is fascinating to botanists because it shares distinctive morphological characteristics with flowering plants, such as broad leaves, woody stems, and flower-like strobili. There are still questions surrounding the relationships within the genus of Gnetum. With that in mind, I focused my work on generating phylogenetic hypotheses, using two molecular data sets: a concatenation of over 60 different chloroplast genes (66,815 base pairs), and the whole chloroplast genome (128,772 base pairs). This allowed me to compare the two phylogenies …

Deep Models For Brain Em Image Segmentation: Novel Insights And Improved Performance, Ahmed Fakhry, Hanchuan Peng, Shuiwang Ji

Computer Science Faculty Publications

Motivation: Accurate segmentation of brain electron microscopy (EM) images is a critical step in dense circuit reconstruction. Although deep neural networks (DNNs) have been widely used in a number of applications in computer vision, most of these models that proved to be effective on image classification tasks cannot be applied directly to EM image segmentation, due to the different objectives of these tasks. As a result, it is desirable to develop an optimized architecture that uses the full power of DNNs and tailored specifically for EM image segmentation.

Results: In this work, we proposed a novel design of DNNs for …