Stochastic Foundations for Single-Cell RNA Sequencing

Author: Gorin, Gennady

Year: 2023

Degree: Dissertation (Ph.D.)

Advisor: Pachter, Lior S.

Committee Members: Shapiro, Mikhail G.; Wang, Zhen-Gang; Chong, Shasha; Ismagilov, Rustem F.; Pachter, Lior S.

Option: Chemical Engineering

DOI: 10.7907/jn6n-x368

Abstract

Single-cell RNA sequencing, which quantifies cell transcriptomes, has seen widespread adoption, accompanied by proliferation of analysis methods. However, there has been relatively little systematic investigation of its best practices and their underlying assumptions, leading to challenges and discrepancies in interpretation. I present a set of generic, principled strategies for modeling the biological and technical components of sequencing experiments and use case studies to motivate their application to sequencing data.

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