Dissertation defense (December 09, 2024): Mateus do Amor Devino Pereira
Student: Mateus do Amor Devino Pereira
Title: A Comparison of scRNA-seq Analysis Workflows for Differentially Expressed Genes Identification in Breast Cancer
Advisors: Eduardo Bezerra da Silva (Advisor) and Kele Teixeira Belloze (Co-advisor)
Committee: Eduardo Bezerra da Silva (PPCIC / CEFET-RJ), Kele Teixeira Belloze (PPCIC / CEFET-RJ), Pedro Henrique González Silva (PPCIC / UFRJ), Fabrício Alves Barbosa da Silva (FIOCRUZ)
Day/Time: December 09, 2024 / 10 a.m
Abstract: In recent years, -omics research has played a major role in understanding cellular biology. In particular, single cell RNA-sequencing data analysis has been successful in drug discovery and biomarker identification of complex diseases, such as cancer. However, when it comes to analyzing scRNA-seq data, several steps in the workflow can be done in different ways. This study provides a comparison of different combinations of techniques in a scRNA-seq workflow, evidencing how each of these steps impact the results. We perform experiments on three datasets of transcriptome data, with each dataset having different magnitudes of number of samples. Our experiments consist of applying a set of preprocessing and clustering techniques to breast cancer scRNA-seq data. We also perform an ablation study to understand how each technique influenced experiment outcomes.
