Publication Date
Fall 11-14-2022
Abstract
Differential gene expression analysis has the potential to discover candidate biomarkers, therapeutic targets, and gene signatures. How to save money when using an unaffordable sample is a practical question. The case-cohort (CCH) study design can blend the economy of case-control studies with the advantages of cohort studies. But it has not been seen in the medical research literature where high-throughput genomic data were involved.
A score test does not need to fit the Cox PH model iteratively; hence, it can save computing time and avoid potential convergence issues. We developed a score test under the CCH design to identify DEGs associated with survival outcomes. We provided asymptotic distribution theory and inferential procedures for the test. We also verified the validity of the inferential procedure in finite samples through simulation studies.
When a permutation-based score test is used for survival outcome-related DEG analysis, the strong PH and probability distribution assumptions do not need to be a concern. However, it cannot be directly applied to the data from a CCH study design because a CCH sample is not a random sample. We developed a procedure to reconstruct a full cohort from a CCH sample and then perform the permutation-based score test on the reconstructed full cohort to identify the DEGs associated with survival outcomes. We evaluated our testing procedures and compared our methods with other existing approaches in terms of the FDR and the power through the simulation study and the application to the real datasets from two cancer-related genomic studies.
Degree Name
Statistics
Level of Degree
Doctoral
Department Name
Mathematics & Statistics
First Committee Member (Chair)
Yan Lu
Second Committee Member
Huining Kang
Third Committee Member
Guoyi Zhang
Fourth Committee Member
Fletcher Christensen
Language
English
Keywords
Differential gene analysis, CCH-based score test, CCH-based Permutation test
Document Type
Dissertation
Recommended Citation
WANG, LIDONG. "Statistical Methods for Differential Gene Expression Analysis under the Case-Cohort Design." (2022). https://digitalrepository.unm.edu/math_etds/184