Rasmus Henningsson’s research interests are centered around high-dimensional biological data in general and Leukemia in particular. He is currently developing new methods for dimension reduction, analysis and visualization of single cell RNA-seq data. He got his PhD degree in applied mathematics at Lund University in 2018, working on dimension reduction, viral evolution and Leukemia.
We present an easy to use and powerful package that enables analysis of Single Cell Expression data in Julia. It is faster and uses less memory than existing solutions since the data is internally represented as expressions of sparse and low rank matrices, instead of storing huge dense matrices. In particular, it efficiently performs PCA (Principal Component Analysis), a natural starting point for downstream analysis, and supports both standard workflows and projections onto a base data set.