Expanding the capabilities of mass cytometry data acquisition and analysis
Abstract/Contents
- Abstract
- There has been an influx of novel single cell data acquisition and analysis methods promising to deepen our understanding of the variation within organ systems in healthy and diseased states. These methods are still in their infancy. Herein, I describe two respective innovations I developed for the acquisition and analysis methods. For the former, I describe an adaption of Proximity Ligation Assay to mass cytometry to add protein-protein and protein-nucleic acid interactions to this type of single cell analysis. For the latter, I describe a computational approach to make continuous comparisons between biological conditions across high-dimensional feature space. These methods provide new avenues of research available within the high-throughput high-parameter single cell analysis paradigm.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2017 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Burns, Tyler J |
|---|---|
| Associated with | Stanford University, Department of Cancer Biology. |
| Primary advisor | Nolan, Garry P |
| Thesis advisor | Nolan, Garry P |
| Thesis advisor | Crabtree, Gerald R |
| Thesis advisor | Plevritis, Sylvia |
| Advisor | Crabtree, Gerald R |
| Advisor | Plevritis, Sylvia |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Tyler J. Burns. |
|---|---|
| Note | Submitted to the Department of Cancer Biology. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2017. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2017 by Tyler Joseph Burns
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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