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.

Creator

• Zhang, Ruosi

Contributors

• Korkin, Dmitry
• Wu, Zheyang

Degree

• MS

Unit

• Bioinformatics & Computational Biology

Publisher

• Worcester Polytechnic Institute

Identifier

• etd-053019-122011

Keyword

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

Advisor

• Wu, Zheyang

Committee

• Korkin, Dmitry

Defense date

• 2019-05-29

Year

• 2019

Date created

• 2019-05-30

Resource type

• Thesis

Rights statement

• In Copyright

Last modified

• 2023-09-13