TITLE: “Model driven design and analysis of quantitative phenotype screens” ABSTRACT: Increasingly, CRISPR screens are coupled with flow cytometry (FACS) to sort cells and quantify the impact of genetic perturbations on a continuous phenotype. While FACS provides much more quantitative information than simple survival screens, it introduces a number of experimental and statistical challenges. Furthermore, as experimentalists push these screens in limited primary cells or in vivo, they lack principled guidelines on how experimental parameters including multiplicity of infection, guide RNA coverage, or…

TITLE: "Is there a Quiescence Histone Code?" ABSTRACT: Many of the cells in our bodies are quiescent, that is, temporarily not dividing. Under certain physiological conditions such as during tissue repair and maintenance, quiescent cells receive the appropriate stimulus and are induced to enter the cell cycle. The ability of cells to successfully transition into and out of a quiescent state is crucial for many biological processes including wound healing, stem cell maintenance, and immunological responses. Histone modifications have been shown…

TITLE: “Integrating single cell omics and deep phenotype data to discover genes underlying cardiometabolic disorders” ABSTRACT: Obesity predisposes to cardiometabolic disorders (CMDs), such as type 2 diabetes, multiple dyslipidemias, and non-alcoholic fatty liver disease (NAFLD). We are interested in how cell-type level gene expression contributes to CMDs and impacts cross talk between cardiometabolic tissues. We hypothesized that obesity-induced inflammatory changes in adipose tissue alter the cell-type composition and key functions of this obesity responsive tissue, which drives ectopic deposition of…

TITLE: “Applications of generalized additive models and copulas to single-cell RNAseq computational method development: PseudotimeDE and scDesign2” ABSTRACT: Part 1: PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data To investigate molecular mechanisms underlying cell state changes, a crucial analysis is to identify differentially expressed (DE) genes along the pseudotime inferred from single-cell RNA-sequencing data. However, existing methods do not account for pseudotime inference uncertainty, and they have either ill-posed p-values or…

TITLE: "DoubletCollection: An R package that integrates cutting-edge computational doublet-detection methods." ABSTRACT: The existence of doublets is a key confounder in single-cell RNA sequencing (scRNA-seq) data analysis. There are several computational methods for detecting doublets from scRNA-seq data. We develop an R package DoubletCollection to integrate the installation and execution of those methods. DoubletCollection also provides a unified interface to perform and visualize downstream analysis after doublet detection. In this talk, we will introduce a protocol of using DoubletCollection to…

TITLE: "Metabolic dependencies of ecDNA and HSR focal amplification modes and plasticity." ABSTRACT: The focal amplification (FA) of genes that support the uncontrolled growth and proliferation of cells (i.e., oncogenes) on homogeneous chromosomal staining regions (HSRs, chromosomal) ans extrachromosomal DNA (ecDNA) is a hallmark of resistant cancers. However, it remains an open question whether oncogene FA is affected by cellular metabolism and by the composition of the tumor microenvironment. This is important because cancers carrying oncogene focal amplifications, particularly on…