School of Public Health

Masters candidate in Biostatistics, Katrina Harper, will present: "Clustering Methods for Single-Cell RNA-Sequencing Data" Plan B Adviser: Erika Helgeson Abstract: As next-generation sequencing technology has advanced, access to single cell RNA-sequencing (scRNA-seq) data has grown along with an interest in its analysis via clustering. scRNA-seq data has two qualities that require attention when it comes to analysis: high-dimensionality and zero inflation (i.e. dropout events). There is not yet a scientific consensus on the best clustering approach to analyzing this type…