Faculty Advisor or Committee Member

Zheyang Wu, Advisor

Faculty Advisor or Committee Member

Dmitry Korkin, Department Head

Identifier

etd-053019-122011

Abstract

The method of combination p-values from multiple tests is the foundation for some studies like meta-analysis and detection of signal. There are tremendous methods have been developed and applied like minimum p-values, Cauchy Combination, goodness-of-fit combination and Fisher’s combination. In this paper, I tested their ability to detect signals which is related to real case in biology to find out significant single-nucleotide polymorphisms (SNPs). I simulated p-values for SNPs logistics regression model and test 7 combination methods’ power performance in different setting conditions. I compared sparse or dense signals, dependent or independent and combine them in gene-level or pathway-level. One method based on Fisher’s combination called Omni-TFisher is ideal for most of the situations. Recent years, genome-wide association studies (GWASs) focused on BMD-related SNPs at gene significance level. In this paper I used Omni-TFisher to analyses real data on haplotype blocks. As a result, haplotype blocks can find more SNPs in non-coding and intergeneric regions than gene-based and save computational complexity. It finds out not only known genes, but also other genes need further verification.

Publisher

Worcester Polytechnic Institute

Degree Name

MS

Department

Bioinformatics and Computational Biology

Project Type

Thesis

Date Accepted

2019-05-30

Accessibility

Restricted-WPI community only

Subjects

GEFOS, haplotype block, Omni-TFisher, p-value combination methods, statistical power

Available for download on Saturday, May 30, 2020

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