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Full-Text Articles in Biostatistics
Novel Bayesian Methodology For The Analysis Of Single-Cell Rna Sequencing Data., Michael Sekula
Novel Bayesian Methodology For The Analysis Of Single-Cell Rna Sequencing Data., Michael Sekula
Electronic Theses and Dissertations
With single-cell RNA sequencing (scRNA-seq) technology, researchers are able to gain a better understanding of health and disease through the analysis of gene expression data at the cellular-level; however, scRNA-seq data tend to have high proportions of zero values, increased cell-to-cell variability, and overdispersion due to abnormally large expression counts, which create new statistical problems that need to be addressed. This dissertation includes three research projects that propose Bayesian methodology suitable for scRNA-seq analysis. In the first project, a hurdle model for identifying differentially expressed genes across cell types in scRNA-seq data is presented. This model incorporates a correlated random …
Sample Size Calculations And Normalization Methods For Rna-Seq Data., Xiaohong Li
Sample Size Calculations And Normalization Methods For Rna-Seq Data., Xiaohong Li
Electronic Theses and Dissertations
High-throughput RNA sequencing (RNA-seq) has become the preferred choice for transcriptomics and gene expression studies. With the rapid growth of RNA-seq applications, sample size calculation methods for RNA-seq experiment design and data normalization methods for DEG analysis are important issues to be explored and discussed. The underlying theme of this dissertation is to develop novel sample size calculation methods in RNA-seq experiment design using test statistics. I have also proposed two novel normalization methods for analysis of RNA-seq data. In chapter one, I present the test statistical methods including Wald’s test, log-transformed Wald’s test and likelihood ratio test statistics for …