Thesis icon

Thesis

Statistical models for single-cell data

Abstract:

The growing use of single-cell gene expression data (scRNA-seq data) has made it possible to more precisely identify cellular subpopulations with distinct characteristics. This offers insight both into normal cellular function and into diseases such as cancer. However, single-cell data presents new challenges which standard clustering and dimensionality reduction methods are not designed to confront. Rather than being drawn from Gaussians as assumed by most models, single-cell datasets con...

Expand abstract

Actions


Access Document


Files:

Authors


More by this author
Institution:
University of Oxford
Research group:
Yau Group
Oxford college:
St Anne's College
Department:
Mathematical,Physical & Life Sciences Division - Statistics
Role:
Author

Contributors

Role:
Supervisor
More from this funder
Funding agency for:
Emma Pierson
Publication date:
2015
Type of award:
MSc by Research
Level of award:
Masters
Awarding institution:
Oxford University, UK
URN:
uuid:2ea412a0-deea-4107-a363-1bbf37cca02e
Local pid:
ora:12263

Terms of use


Metrics


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP