Bioinformatics Commons^™

Estimation Of Variation For High-Throughput Molecular Biological Experiments With Small Sample Size, Danni Yu

Open Access Dissertations

Motivation: In the quantification of molecular components, a large variation can affect and even potentially mislead the biological conclusions. Meanwhile, the high-throughput experiments often involve a small number of samples due to the limitation of cost and time. In such cases, the stochastic information may dominate the outcome of an experiment because there may not be enough samples to present the true biological information. It is challenging to distinguish the changes in phenotype from the stochastic variation.

Methods: Since the biological molecules have been quantified with different technologies, different statistical methods are required. Focusing on three types of important high-throughput …

Statistical Models For Gene And Transcripts Quantification And Identification Using Rna-Seq Technology, Han Wu

Open Access Dissertations

RNA-Seq has emerged as a powerful technique for transcriptome study. As much as the improved sensitivity and coverage, RNA-Seq also brings challenges for data analysis. The massive amount of sequence reads data, excessive variability, uncertainties, and bias and noises stemming from multiple sources all make the analysis of RAN-Seq data difficult. Despite much progress, RNA-Seq data analysis still has much room for improvement, especially on the quantification of gene and transcript expression levels. The quantification of gene expression level is a direct inference problem, whereas the quantification of the transcript expression level is an indirect problem, because the label of …