UC Riverside

The revolutionary advancement in Next-Generation Sequencing (NGS) technology has transformed genomics research by enabling the analysis of the complete genome, transcriptome, and epigenome of samples. However, the high-throughput nature of sequencing has resulted in a deluge of big data, leading to significant heterogeneity stemming from various platforms and procedures. To tackle these challenges, sophisticated biostatistical models and bioinformatics pipelines are necessary. This dissertation presents innovative approaches and techniques for detecting biomarkers and developing prediction models for complex human traits utilizing NGS technology.

In Chapter 1, this dissertation provides a comprehensive background introduction to the disease traits, molecular markers, and statistical models covered in subsequent chapters. Chapter 2 focuses on integrating omics data using a hierarchical structure following the central dogma to predict clinical outcomes for patients with prostate cancer. We propose an innovative two-layer LASSO regression model that structurally connects transcriptome, MiRome, and methylome data with disease outcomes, revealing potential associations between HPV and prostate cancer. In Chapter 3, we demonstrate a global difference in the distribution of multiple types of alternative splicing events in aggressive vs. indolent chronic lymphocytic leukemia (CLL) and leverage splicing profiles for the first time to predict disease outcomes. Our results highlight a path for integrating omics data to design a better prognostic model in CLL. In Chapter 4, we present a cost-effective methodology to study DNA recombination in single sperm cells of a human population. Our proposed crossover detection pipeline analyzes high-depth ($>50$X) whole genome sequencing data and paired low-depth ($\sim 1$X) whole genome sequencing data for five single sperm cells to phase the individual genomes at the chromosome scale and detect crossovers in these sperm cells. Our analysis of 37 normal males and 16 males with asthenospermia reveals a deficiency in forming crossovers in individuals with the disease. In Chapter 5, we offer a summary and in-depth discussion of the key findings presented in each study of the dissertation.