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Articles 1 - 9 of 9
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Statistical Methods For Gene Selection And Genetic Association Studies, Xuewei Cao
Statistical Methods For Gene Selection And Genetic Association Studies, Xuewei Cao
Dissertations, Master's Theses and Master's Reports
This dissertation includes five Chapters. A brief description of each chapter is organized as follows.
In Chapter One, we propose a signed bipartite genotype and phenotype network (GPN) by linking phenotypes and genotypes based on the statistical associations. It provides a new insight to investigate the genetic architecture among multiple correlated phenotypes and explore where phenotypes might be related at a higher level of cellular and organismal organization. We show that multiple phenotypes association studies by considering the proposed network are improved by incorporating the genetic information into the phenotype clustering.
In Chapter Two, we first illustrate the proposed GPN …
Knowledge Discovery On The Integrative Analysis Of Electrical And Mechanical Dyssynchrony To Improve Cardiac Resynchronization Therapy, Zhuo He
Dissertations, Master's Theses and Master's Reports
Cardiac resynchronization therapy (CRT) is a standard method of treating heart failure by coordinating the function of the left and right ventricles. However, up to 40% of CRT recipients do not experience clinical symptoms or cardiac function improvements. The main reasons for CRT non-response include: (1) suboptimal patient selection based on electrical dyssynchrony measured by electrocardiogram (ECG) in current guidelines; (2) mechanical dyssynchrony has been shown to be effective but has not been fully explored; and (3) inappropriate placement of the CRT left ventricular (LV) lead in a significant number of patients.
In terms of mechanical dyssynchrony, we utilize an …
Construction And Analysis Of Genetic Regulatory Networks With Rna-Seq Data From Arabidopsis Thaliana, Tessa Kriz
Construction And Analysis Of Genetic Regulatory Networks With Rna-Seq Data From Arabidopsis Thaliana, Tessa Kriz
Dissertations, Master's Theses and Master's Reports
Reconstruction of gene regulatory networks (GRNs) is a fundamental aspect of genetic engineering and provides a deeper understanding of the biological processes of an organism. Two methods were implemented to reconstruct the gene regulatory networks of Arabidopsis thaliana under two treatments: methyl jasmonate (MeJa) and salicylic acid (SA). The Joint Reconstruction of multiple Gene Regulatory Networks (JRmGRN) method was utilized to construct a joint network for identifying hub genes common to both conditions in addition to networks specific to each condition. The Differential Network Analysis with False Discover Rate Control method constructed a network of connections unique to only one …
Statistical Methods In Genetic Studies, Cheng Gao
Statistical Methods In Genetic Studies, Cheng Gao
Dissertations, Master's Theses and Master's Reports
This dissertation includes three Chapters. A brief description of each chapter is organized as follows.
In Chapter 1, we proposed a new method, called MF-TOWmuT, for genome-wide association studies with multiple genetic variants and multiple phenotypes using family samples. MF-TOWmuT uses kinship matrix to account for sample relatedness. It is worth mentioning that in simulations, we considered hidden polygenic effects and varied the proportion of variance contributed by it to generate phenotypes. Simulation studies show that MF-TOWmuT can preserve the type I error rates and is more powerful than several existing methods in different simulation scenarios, MFTOWmuT is also quite …
Statistical Methods For Joint Analysis Of Multiple Phenotypes And Their Applications For Phewas, Xueling Li
Statistical Methods For Joint Analysis Of Multiple Phenotypes And Their Applications For Phewas, Xueling Li
Dissertations, Master's Theses and Master's Reports
Genome-wide association studies (GWAS) have successfully detected tens of thousands of robust SNP-trait associations. Earlier researches have primarily focused on association studies of genetic variants and some well-defined functions or phenotypic traits. Emerging evidence suggests that pleiotropy, the phenomenon of one genetic variant affects multiple phenotypes, is widespread, especially in complex human diseases. Therefore, individual phenotype analyses may lose statistical power to identify the underlying genetic mechanism. Contrasting with single phenotype analyses, joint analysis of multiple phenotypes exploits the correlations between phenotypes and aggregates multiple weak marginal effects and is therefore likely to provide new insights into the functional consequences …
Statistical Methods For Detecting Causal Rare Variants And Analyzing Multiple Phenotypes, Xinlan Yang
Statistical Methods For Detecting Causal Rare Variants And Analyzing Multiple Phenotypes, Xinlan Yang
Dissertations, Master's Theses and Master's Reports
This dissertation includes two papers with each distributed in one chapter. To date, genome-wide association studies (GWAS) have identified a large number of common variants that are associated with complex diseases successfully. However, the common variants identified by GWAS only account for a small proportion of trait heritability. Many studies showed that rare variants could explain parts of the missing heritability. Since the well-developed common variant detecting methods are underpowered for rare variant association tests unless sample sizes or effect sizes are very large, investigation the roles of rare variants in complex diseases presents substantial challenges. In chapter 1, we …
Statistical Methods For Analyzing Multivariate Phenotypes And Detecting Rare Variant Associations, Huanhuan Zhu
Statistical Methods For Analyzing Multivariate Phenotypes And Detecting Rare Variant Associations, Huanhuan Zhu
Dissertations, Master's Theses and Master's Reports
This dissertation includes four papers with each distributed in one chapter.
In chapter 1, I compared the performance of eight multivariate phenotype association tests. The motivation to conduct this power comparison paper is as follows. For nearly 15 years, genome-wide association studies (GWAS) have been widely used to identify genetic variants associated with human diseases and traits. GWAS typically investigate genetic variants for a predefined phenotype, thus fail to identify weak but important effects. In recent years, many multivariate association tests have been developed. However, there is a lack of comprehensive summary of such kinds of approaches. To fill this …
Joint Analysis Of Multiple Phenotypes In Association Studies, Xiaoyu Liang
Joint Analysis Of Multiple Phenotypes In Association Studies, Xiaoyu Liang
Dissertations, Master's Theses and Master's Reports
Genome-wide association studies (GWAS) have become a very effective research tool to identify genetic variants of underlying various complex diseases. In spite of the success of GWAS in identifying thousands of reproducible associations between genetic variants and complex disease, in general, the association between genetic variants and a single phenotype is usually weak. It is increasingly recognized that joint analysis of multiple phenotypes can be potentially more powerful than the univariate analysis, and can shed new light on underlying biological mechanisms of complex diseases. Therefore, developing statistical methods to test for genetic association with multiple phenotypes has become increasingly important. …
Analysis Of Data From A Study To Identify Potential Biomarkers To Indicate Renal Injury, Mitchell D. Tahtinen
Analysis Of Data From A Study To Identify Potential Biomarkers To Indicate Renal Injury, Mitchell D. Tahtinen
Dissertations, Master's Theses and Master's Reports
Ureteropelvic junction obstruction is a disease in which flow from the kidney to the bladder is obstructed for extended periods of time causing irreversible damage to the kidney. Current tests to detect kidney damage caused by obstruction are not effective until significant damage occurs. The purpose of this report is to identify a panel of biomarkers in urine to detect kidney damage earlier by analyzing data collected from a two-part study. Currently, two established urinary biomarkers to indicate kidney damage are NGAL and KIM-1. Biomarkers of interest in this study are CD13, CD10, and CD26. Results from the linear mixed …