Laleh Haghverdi
EMBL Heidelberg, Meyerhofstraße , Germany
Title: High-dimensional Single Cell Gene Expression Data and Batch Effect Corrections
Biography
Biography: Laleh Haghverdi
Abstract
Emerging about a decade ago, single cell genes expression measurement technologies have facilitated the study of heterogeneous populations of cells such as in development and cell differentiation. Single cell Ribonucleic acid sequencing (scRNA-Seq) techniques can measure the expression level of several thousand genes at the single cell level for millions of cells. Increasingly used by several laboratories, the technique provides a big amount of data which opens new opportunities for knowledge extraction using new machine learning and computational methods. I will discuss the properties of high-dimensional data which needs to be taken care of when dealing with such big expression data, and discuss in an instance on how high-dimension properties allowed us to develop a new method for batch effects correction and data integration across several laboratories.