RNA velocity analysis for Pertrub-Seq

Abstract

Recent developments in single-cell RNA seq and CRISPR based perturbations have enabled researchers to carry out hundreds of perturbation experiments in a pooled format in an experimental approach called Perturb-Seq [7]. Prior analysis of Perturb-Seq measured the overall effect of a perturbation on each gene, however it remains difficult to capture temporal responses to a perturbation. In this thesis, we compare the effectiveness of three RNA velocity informed models and two cell-cell similarity based models in providing a pseudo-temporal ordering of cells. We find pseudotime estimated with the dynamical model for computing velocity provides the most reliable ordering of cells. We use this pseudo-temporal ordering to bin cells into three time resolved groups and compute the effect of a perturbation at each time point. This analysis provides a promising start to understanding the temporal effects of a perturbation.