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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...

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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Research group:
Yau Group
Oxford college:
St Anne's College
Role:
Author

Contributors

Division:
MPLS
Department:
Statistics
Role:
Supervisor
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Funding agency for:
Pierson, E
Publication date:
2015
Type of award:
MSc by Research
Level of award:
Masters
Awarding institution:
Oxford University, UK
Language:
English
Keywords:
Subjects:
UUID:
uuid:2ea412a0-deea-4107-a363-1bbf37cca02e
Local pid:
ora:12263
Deposit date:
2015-09-24

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