Statistical Methods For Rna Sequencing Data
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Statistical Methods for RNA-sequencing Data
Author | : Rhonda Bacher |
Publisher | : |
Total Pages | : 0 |
Release | : 2017 |
Genre | : |
ISBN | : |
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Major methodological and technological advances in sequencing have inspired ambitious biological questions that were previously elusive. Addressing such questions with novel and complex data requires statistically rigorous tools. In this dissertation, I develop, evaluate, and apply statistical and computational methods for analysis of high-throughput sequencing data. A unifying theme of this work is that all these methods are aimed at RNA-seq data. The first method focuses on characterizing gene expression in RNA-seq experiments with ordered conditions. The second focuses on single-cell RNA-seq data, where we develop a method for normalization to account for a previously unknown technical artifact in the data. Finally, we develop a simulation in order to recapitulate the source of the artifact [in silico].
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