Algorithms for differential analysis of cellular composition in single-cell perturbation experiments

Abstract

Advancements in multiplexing techniques have enabled the application of single-cell genomic methods to comprehensively study the effects of high-throughput perturbation experiments at a whole-embryo scale. Such analyses aim to pinpoint key genes, cell types, and signaling pathways that control cell fate decisions during development. However, there is a lack of statistically principled tools for measuring how cell types shift after perturbations (genetic, chemical, or environmental) and identifying which genes regulate those transitions. In this thesis, I introduce two new software packages for studying single-cell perturbation experiments. Hooke is a new software package that uses Poisson-Lognormal models to perform differential analysis of cell abundances for perturbation experiments read out by single-cell RNA-seq. This versatile framework allows users to 1) perform multivariate statistical regression to describe how perturbations alter the relative abundances of each cell state and 2) describe how all pairs of states co-vary as a parsimonious network of partial correlations. To demonstrate Hooke’s utility, we analyzed a single-cell atlas of zebrafish organogenesis that includes wild-type and genetic perturbations at whole-embryo scale across multiple time points. This method identified novel genetic requirements for relatively rare cell types in the embryonic kidney. Platt is another new software package that uses Hooke's outputs to construct lineage graphs based on the covariation of cell type counts in time series and perturbation data. These graphs help identify candidate transcription factors important in lineage specification and organize differential abundance results into direct and indirect effects. With Platt, we study the impact of knocking out the lmx1b, a homeobox transcription factor with specific expression in multiple lineages. Both packages aim to fill a critical gap by allowing users to characterize how their experimental perturbations alter cells' proportions and molecular states in complex tissues or whole embryos.