Dissertation Defense - Nick Lytal
Normalization Methods on Single-Cell RNA-Seq Data and Metagenomics Data
DNA and RNA sequencing analyses explain biological processes and the relationships of cells. Technological advancements have given rise to new studies, including single-cell RNA sequencing and metagenomics. A process known as normalization is required to adjust for uneven sample sizes and technical noise common in such data sets. In this dissertation, I present two novel normalization methods: one for single-cell RNA sequencing and one for metagenomics sequencing. I begin with a summary of existing single-cell RNA sequencing methods before introducing my own, Weighted Between Groups Normalization (WeBe). This approach uses external spike-in RNAs to establish relationships within and between cell conditions. I also present 2-Stage Scaling Normalization (2SS), a metagenomics-based method that first normalizes within conditions, then identifies a set of stable features across all cells to normalize across conditions. I use simulation studies and real data analysis to demonstrate the effectiveness of each new method.