Contributor
Xinlei Wang, Daniel F. Heitjan, Raanju Sundararajan, Tao Wang
Subject Area
Statistics
Abstract
This dissertation consists of three chapters: 1) Comparative Analysis of Dimension Reduction Methods for Cytometry by Time-of-Flight Data, 2) Integrative Single-Cell Analysis Using Regularized Multitasking Graphical Attention Model with CySCI, and 3) BiGER for Bayesian Rank Aggregation in Genomics with Extended Ranking Schemes.
While experimental and informatic techniques around single cell sequencing (scRNA-seq) are advanced, research around mass cytometry (CyTOF) data analysis has severely lagged behind. This calls for the evaluation and development of computational methods specific for CyTOF data. We first benchmarked dimension reduction methods for CyTOF in Chapter 1. Then, we developed an integrative method for multimodal single-cell data with applications in CyTOF and scRNA. In chapter 3, we tackled a downstream task with the rank aggregation of gene lists using a Bayesian model.
Degree Date
Summer 2025
Document Type
Dissertation
Degree Name
Ph.D.
Department
Department of Statistics and Data Science
Advisor
Xinlei Wang
Second Advisor
Daniel F. Heitjan
Third Advisor
Raanju Sundararajan
Fourth Advisor
Tao Wang
Number of Pages
195
Format
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Recommended Citation
Wang, Kaiwen, "The Development of Advanced Statistical Methods for Complex Big Data" (2025). Statistical Science Theses and Dissertations. 52.
https://scholar.smu.edu/hum_sci_statisticalscience_etds/52
