Researcher(s)
- Aeila Chesley, Biological Sciences, University of Delaware
Faculty Mentor(s)
- Arit Ghosh, Flow Cytometry Core, University of Delaware
Abstract
Multi-omic single cell RNA sequencing experiments produce large amounts of data, and bottleneck for rapid analysis of such large discovery-based datasets. Running bioinformatics analyses of scRNA-seq datasets requires the use of specialized programming languages such as R and extensive knowledge of code troubleshooting which can be intimidating for researchers since the skills required to navigate these programs are not trivial. Such instances have brought out the need for easy to navigate interfaces that researchers and wet-lab scientists with relatively no bioinformatics experience can use with little extra training. The Cellismo platform from BD Biosciences is a free software that provides a graphical user interface for analyzing large datasets from single cell sequencing experiments. With a variety of built-in features and room for manipulation the Cellismo platform can bridge the gap for wet-lab scientists. This project will highlight the capabilities of the Cellismo platform for analyzing single cell RNA sequencing data by demonstrating various capabilities such as UMAP generation, differential gene expression volcano plots and heatmaps that can be generated from within the platform.