Bayesian assembly of reads from high throughput sequencing
Abstract/Contents
- Abstract
- The high-throughput sequencing revolution allows us to take millions of noisy short reads from the DNA in a sample, essentially taking a snapshot of the genomic material in the sample. To recover the true genomes, these reads are assembled by algorithms exploiting their high coverage and overlap. I focus on two scenarios for sequence assembly. The first is de novo assembly, where the reads come from an unknown and diverse population of genomes. The second is variant assembly, where the reads come from short but clonally related genomes, only slightly mutated from each other. In both cases I use the same principled Bayesian approach to design an algorithm that uncovers the composition of the genomic sequences that produced the reads. I will demonstrate the algorithms' performance on real data taken from various metagenomic environments, as well as the immune system B cells. On that latter dataset, collected from 10 organ donors each providing 4 tissue samples, the results show evidence of clone migration between tissues and provide new insights on the organization of the immune system.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2012 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Laserson, Jonathan Daniel |
|---|---|
| Associated with | Stanford University, Computer Science Department |
| Primary advisor | Koller, Daphne |
| Thesis advisor | Koller, Daphne |
| Thesis advisor | Batzoglou, Serafim |
| Thesis advisor | Fire, Andrew Zachary |
| Advisor | Batzoglou, Serafim |
| Advisor | Fire, Andrew Zachary |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Jonathan Laserson. |
|---|---|
| Note | Submitted to the Department of Computer Science. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2012. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2012 by Jonathan Daniel Laserson
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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