Short talk: A graphical model for single-cell RNA-seq data

A graphical model for single-cell RNA-seq data

Davide Risso University of Padova

Abstract

Recent technological advances in molecular biology allow the sequencing of RNA from individual cells (single-cell RNA-seq). Typically, the genes whose expressions are differential between cell states or across experimental conditions are identified with univariate (gene-wise) models. However, it may be beneficial to explicitly account for gene dependencies in multivariate statistical models. In this talk, I will introduce a graphical model for single-cell RNA-seq and show how to use it to explore the dynamics of transcription factors in development. The approach is currently implemented in the R package available at https://github.com/drisso/learn2count.

Keywords: NA