Computational methods for cytometry

Resource type
Thesis type
(Thesis) Ph.D.
Date created
2022-04-28
Authors/Contributors
Author: Yue, Alice
Abstract
Flow cytometry (FCM) is a high-throughput single-cell biotechnology commonly used to study the immune system in clinical and research settings. We present solutions to two problems in an FCM data analysis pipeline. The first problem is to identify cell populations within FCM samples. The second problem is to pinpoint the biomarkers or cell populations that can be used to help classify FCM samples (e.g. diseased vs healthy). This thesis covers topics in computational biology and is intended for readers with basic knowledge in the field.
Document
Extent
156 pages.
Identifier
etd21981
Copyright statement
Copyright is held by the author(s).
Permissions
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Supervisor or Senior Supervisor
Thesis advisor: Libbrecht, Maxwell
Language
English
Member of collection
Download file Size
etd21981.pdf 7.45 MB

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