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Thesis - University Access Only
Master of Science (MS)
Mathematics and Statistics
Stem cell research has potential for a variety of medicinal uses. This thesis investigates the expression patterns of genes during embryonic stem cell differentiation in mice. The data, obtained from a previously published study, was reanalyzed and follows mouse embryonic stem cell (ESC) lines, J1, R1, and V6.5, over 14 days. Oligonucleotide DNA microarrays were used to measure gene expression levels. In contrast to the previous analysis, this paper used exploratory data analysis and the full time course. This paper hypothesizes that there are differences and similarities in gene expression dynamics in ESC differentiation among the lines. The data is examined again via Quality Assurance to assess feasibility for functional analysis. Filtration removes genes that are not differentially expressed during the time course. Hierarchical clustering is used to highlight correlation between genes. K-means clustering is used to segment the genes into 6 clusters for each ESC line. These clusters are aligned per ESC line and investigated by comparing the clusters’ gene lists. The K-mean clustering groups are then used for functional enrichment analysis using the Database for Annotation, Visualization, and Integrated Discovery.
Library of Congress Subject Headings
Embryonic stem cells
Includes bibliographical references (pages 110-114)
Number of Pages
South Dakota State University
In Copyright - Educational Use Permitted
Whipple, Matthew, "Cluster Analysis of Gene Expression Profiles Stem Cell Differentiation in Mice" (2013). Electronic Theses and Dissertations. 1685.