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Full-Text Articles in Life Sciences

Multivariate Statistical Modeling For Radio-Genomics Study, Tiantian Zeng Jan 2022

Multivariate Statistical Modeling For Radio-Genomics Study, Tiantian Zeng

Theses and Dissertations--Statistics

Radiogenomics is a new direction in cancer research that focuses on the associations among radiomics, genomics and clinical outcome. Currently, the major challenge for Radiogenomics lies in the effective integration of genomics and imaging data for promising clinical outcome prediction. Herein, we propose a multivariate joint model that can integrate imaging and genomic data for better predicting the clinical outcome. Specifically, we jointly consider two multivariate group lasso models, one regresses imaging features on genomic features, and the other regresses patient’s clinical outcome on genomic features. An L1 penalty term is introduced for each variable, and weight in the penalty …


Statistical Approaches Of Gene Set Analysis With Quantitative Trait Loci For High-Throughput Genomic Studies., Samarendra Das Dec 2020

Statistical Approaches Of Gene Set Analysis With Quantitative Trait Loci For High-Throughput Genomic Studies., Samarendra Das

Electronic Theses and Dissertations

Recently, gene set analysis has become the first choice for gaining insights into the underlying complex biology of diseases through high-throughput genomic studies, such as Microarrays, bulk RNA-Sequencing, single cell RNA-Sequencing, etc. It also reduces the complexity of statistical analysis and enhances the explanatory power of the obtained results. Further, the statistical structure and steps common to these approaches have not yet been comprehensively discussed, which limits their utility. Hence, a comprehensive overview of the available gene set analysis approaches used for different high-throughput genomic studies is provided. The analysis of gene sets is usually carried out based on …


Statistical Methods For Two Problems In Cancer Research: Analysis Of Rna-Seq Data From Archival Samples And Characterization Of Onset Of Multiple Primary Cancers, Jialu Li May 2017

Statistical Methods For Two Problems In Cancer Research: Analysis Of Rna-Seq Data From Archival Samples And Characterization Of Onset Of Multiple Primary Cancers, Jialu Li

Dissertations & Theses (Open Access)

My dissertation is focused on quantitative methodology development and application for two important topics in translational and clinical cancer research.

The first topic was motivated by the challenge of applying transcriptome sequencing (RNA-seq) to formalin-fixation and paraffin-embedding (FFPE) tumor samples for reliable diagnostic development. We designed a biospecimen study to directly compare gene expression results from different protocols to prepare libraries for RNA-seq from human breast cancer tissues, with randomization to fresh-frozen (FF) or FFPE conditions. To comprehensively evaluate the FFPE RNA-seq data quality for expression profiling, we developed multiple computational methods for assessment, such as the uniformity and continuity …


Annotation Tools For Multivariate Gene Set Testing Of Non-Model Organisms, Russell K. Banks May 2015

Annotation Tools For Multivariate Gene Set Testing Of Non-Model Organisms, Russell K. Banks

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Microarray chip technology enables researchers to obtain measures of gene activity for essentially all genes in an organism. After grouping genes into biologically meaningful sets, researchers employ certain statistical tests to identify which gene sets (biological processes) show different levels of activity across different treatment groups. The idea is to identify which biological processes are significantly affected by a certain treatment/condition in a given organism.

Non-model organisms (such as sheep) are not widely studied so gene set membership information is not always readily accessible. This thesis work utilizes two microarray studies involving sheep to provide researchers with working examples of …


High-Throughput Data Analysis: Application To Micronuclei Frequency And T-Cell Receptor Sequencing, Mateusz Makowski Jan 2015

High-Throughput Data Analysis: Application To Micronuclei Frequency And T-Cell Receptor Sequencing, Mateusz Makowski

Theses and Dissertations

The advent of high-throughput sequencing has brought about the creation of an unprecedented amount of research data. Analytical methodology has not been able to keep pace with the plethora of data being produced. Two assays, ImmunoSEQ and the cytokinesisblock micronucleus (CBMN), that both produce count data and have few methods available to analyze them are considered.

ImmunoSEQ is a sequencing assay that measures the beta T-cell receptor (TCR) repertoire. The ImmunoSEQ assay was used to describe the TCR repertoires of patients that have undergone hematopoietic stem cell transplantation (HSCT). Several different methods for spectratype analysis were extended to the TCR …