Alternative splicing analysis using RNA-seq data
Abstract/Contents
- Abstract
- A single gene may produce multiple variants of a protein called isoforms. This process is mediated by alternative splicing of the mRNA transcript. We discuss some of the challenges inherent in the tasks of isoform quantification and novel isoform discovery on a given sample, and steps we have taken to address these challenges. In particular, in the first portion of this thesis we discuss the isoform quantification problem and give a technical condition describing under what conditions it is identifiable. In the second half of this thesis, we present a mathematical formulation of a novel approach to solving the isoform discovery problem. We show that our approach performs well on simulated data under both uniform read sampling and significantly biased sampling, and that it also returns a reasonable result on several test genes taken from an actual RNA-seq data set.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2010 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Hiller, David James |
|---|---|
| Associated with | Stanford University, Department of Statistics |
| Primary advisor | Wong, Wing Tak Jack Wong |
| Thesis advisor | Wong, Wing Tak Jack Wong |
| Thesis advisor | Olshen, Richard A, 1942- |
| Thesis advisor | Owen, Art B |
| Advisor | Olshen, Richard A, 1942- |
| Advisor | Owen, Art B |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | David James Hiller. |
|---|---|
| Note | Submitted to the Department of Statistics. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2010. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2010 by David James Hiller
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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