Date of Award
2020
Publisher
North Dakota State University
Document Type
Thesis
Degree Awarded
Master of Science (MS)
Department
Statistics
College
Science and Mathematics
Faculty Advisor
Orr, Megan
Description
Both microarray and RNA-seq technologies are powerful tools which are commonly used in differential expression (DE) analysis. Gene expression levels are compared across treatment groups to determine which genes are differentially expressed. With both technologies, filtering and normalization are important steps in data analysis. In this thesis, real datasets are used to compare current analysis methods of two-color microarray and RNA-seq experiments. A variety of filtering, normalization and statistical approaches are evaluated. The results of this study show that although there is still no widely accepted method for the analysis of these types of experiments, the method chosen can largely impact the number of genes that are declared to be differentially expressed.
Recommended Citation
Speicher, Mackenzie Rosa Marie, "A Comparison of Filtering and Normalization Methods in the Statistical Analysis of Gene Expression Experiments" (2020). Statistics. 18.
https://digitalcommons.ndsu.edu/stats/18
Rights
NDSU policy 190.6.2
Rights Link
https://www.ndsu.edu/fileadmin/policy/190.pdf
Handle Identifier
https://hdl.handle.net/10365/32041