The Herbert and Florence Irving Institute for Cancer Dynamics will continue its seminar series on the topic of mathematical sciences underpinning cancer research during the 2022-2023 academic year. The monthly seminars take place on the third Wednesday of the month, 2:00-3:00 PM EST. The presentations are open to the Columbia community (in person and online) and to researchers outside Columbia (via Zoom).

On Wednesday, December 14th (2:00 PM ET), IICD welcomes Brian Cleary, PhD, Assistant Professor of Computing and Data Science, Boston University. Seminar hosted by Sanja Vickovic, PhD. The seminar will take place in person in Schermerhorn Hall 603 (Morningside Heights campus). If you wish to attend the seminar remotely, please register using the following link: https://columbiauniversity.zoom.us/meeting/register/tJcvc--rpjooEtMjU4HXdPBczV17C5nhcuXn

Title: Efficient Screens for Regulatory Circuits with Compressed Perturb-seq; an Algorithmic Lens on Functional Genomics

Abstract: Pooled CRISPR screens with single-cell RNA-seq readout (Perturb-seq) have emerged as a key technique in functional genomics but are limited in scale by cost and combinatorial complexity. Here, we describe an experimental and computational framework for “compressed” Perturb-seq, which substantially reduces the cost of the experiment without sacrificing accuracy. The conceptual core of this framework is a composite experiment, which reflects the average outcome of a random subset of "normal" experiments. We propose small changes to the conventional experimental protocol that enable measuring multiple perturbations in each cell or droplet. Then, we develop a new computational method to deconvolve individual perturbation effects from the resulting measurements by leveraging the modular and sparse structure of transcriptional data. This reformulates latent factors (i.e., a module), rather than genes, as the fundamental unit of interrogation. Applying compressed Perturb-seq to 598 genes in the immune response to bacterial LPS, we achieve the same accuracy as conventional Perturb-seq at >5- fold reduced cost, with greater power to learn genetic interactions. We identify known and novel regulators of immune responses and uncover constrained genes with downstream targets enriched for
immune disease heritability, including many missed by existing GWAS or trans-eQTL studies. Our framework enables new scales of interrogation for a foundational method in functional genomics.

Bio: Brian Cleary is an Assistant Professor in the Faculty of Computing and Data Sciences, the Department of Biomedical Engineering, and the Department of Biology and is a Core Faculty Member of the Program in Bioinformatics and the Biological Design Center at Boston University. Professor Cleary received his PhD in Computational and Systems Biology from MIT, and was an independent Broad Fellow at the Broad Institute before moving to BU.