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Statistical Methods for Biological and Relational Data
Anderson, Sarah G

2013, Master of Science, Ohio State University, Biostatistics.
Methods for biological and relational data have pose challenges for statistical modeling. For biological data, gene expression data have high-dimensionality, and T-cell receptor (TCR) data under-sample receptor populations. For relational data, there are dependencies among the observations. This thesis outlines statistical methods for biological and relational data. The methods include classification, multiple testing and social networking. The models for classification are applied to gene expression data. The first method looks at variable selection to show the usefulness of sequential classification and regression trees to more advance methods. The second method uses Monte Carlo methods to calculate a rank for variable selection using supervised classification. Multiple testing methods are applied to gene expression and TCR data. The first method for gene expression looks at strong control of the familywise error rate without the assumption of the subset pivotality property, which is generally not met for gene expression data. For TCRs, the method extends the Poisson-lognormal model to the bivariate case to simultaneously analyze pairs of repertoires. The relational data uses social networking methods. The first uses exponential random graph models (ERGMs) with the application to political science. Solutions to two limitation of ERGMs, non-binary ties and longitudinal, are presented in examples. The last method proposes a latent position cluster model, an extension of latent class models that models clustering.
Hong Zhu (Advisor)
Abigail Shoben (Committee Member)

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Anderson, S. (2013). Statistical Methods for Biological and Relational Data. (Electronic Thesis or Dissertation). Retrieved from https://etd.ohiolink.edu/

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Anderson, Sarah. "Statistical Methods for Biological and Relational Data." Electronic Thesis or Dissertation. Ohio State University, 2013. OhioLINK Electronic Theses and Dissertations Center. 16 Dec 2017.

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Anderson, Sarah "Statistical Methods for Biological and Relational Data." Electronic Thesis or Dissertation. Ohio State University, 2013. https://etd.ohiolink.edu/

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