Award Date

5-15-2025

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Life Sciences

First Committee Member

Mira Han

Second Committee Member

Jingchun Chen

Third Committee Member

Matthew Meiselman

Fourth Committee Member

Lukasz Sznajder

Number of Pages

58

Abstract

Transcript isoforms arising from alternative splicing events can contribute to the development of a cell’s identity and function and overall protein diversity. Peripheral blood is a useful model to study and evaluate computational methods for alternative splicing detection due to its abundant data across various sequencing protocols. The alternative splicing events across different blood cell types have not been completely identified and detecting alternative splicing through short read sequencing is still a challenging problem. Here, we propose to integrate multiple bulk RNA-seq datasets of purified blood cells using a novel integration method to identify the cell-type specific alternative splicing events in different blood cell types. We applied the detection methods to three data sets across two cell type comparisons. We show that we can integrate the results of two independent approaches of alternative splicing detection that were previously considered too different to be reconciled. The results show very little concordance between the different approaches. It also allowed us to identify the few confident events that are commonly detected by both approaches. The integration allowed us to re-analyze past studies and produce a comprehensive list of alternatively spliced events based on multiple software. In conclusion, this work achieves an overarching list of significant parts/events associated with different cell types by integrating across multiple softwares and datasets.

Keywords

alternative splicing; immune cells; splicing detection; transcript isoforms

Disciplines

Biology

File Format

pdf

File Size

11100 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Rights

IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

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Biology Commons

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