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Articles 31 - 32 of 32
Full-Text Articles in Applied Statistics
Statistics In The Billera-Holmes-Vogtmann Treespace, Grady S. Weyenberg
Statistics In The Billera-Holmes-Vogtmann Treespace, Grady S. Weyenberg
Theses and Dissertations--Statistics
This dissertation is an effort to adapt two classical non-parametric statistical techniques, kernel density estimation (KDE) and principal components analysis (PCA), to the Billera-Holmes-Vogtmann (BHV) metric space for phylogenetic trees. This adaption gives a more general framework for developing and testing various hypotheses about apparent differences or similarities between sets of phylogenetic trees than currently exists.
For example, while the majority of gene histories found in a clade of organisms are expected to be generated by a common evolutionary process, numerous other coexisting processes (e.g. horizontal gene transfers, gene duplication and subsequent neofunctionalization) will cause some genes to exhibit a …
Genetic Association Testing Of Copy Number Variation, Yinglei Li
Genetic Association Testing Of Copy Number Variation, Yinglei Li
Theses and Dissertations--Statistics
Copy-number variation (CNV) has been implicated in many complex diseases. It is of great interest to detect and locate such regions through genetic association testings. However, the association testings are complicated by the fact that CNVs usually span multiple markers and thus such markers are correlated to each other. To overcome the difficulty, it is desirable to pool information across the markers. In this thesis, we propose a kernel-based method for aggregation of marker-level tests, in which first we obtain a bunch of p-values through association tests for every marker and then the association test involving CNV is based on …