Single-cell trajectories from omics/CRISPR tiling

Luca Pinello & Jonathan Hsu
MGH, HMS, Broad & MIT Bioengineering; Pinello, Joung, Collins Labs
A deconvolution framework for the analysis of CRISPR tiling screen data

Abstract: The advent of programmable genome editing using CRISPR-based technologies has allowed for high-throughput functional interrogation of non-coding elements throughout the genome. Functional mapping can be achieved by densely tiling single guide RNAs (sgRNAs) across a non-coding region of interest, where each sgRNA enables linking of a unique genomic location to an observable phenotype. Here we present CRISPR-SURF, a generalizable deconvolution framework, to discover and dissect non-coding regulatory elements from the analysis of CRISPR tiling screen data. Luca Pinello will open up the talk by motivating why people are excited about CRISPR tiling screen and describing the key ideas and challenges. Jonathan Hsu will dive into the details of the proposed deconvolution framework - the method at the heart of CRISPR-SURF - and discuss an efficient implementation for it. Finally, we will discuss future directions for the use of CRISPR-Cas tiling screens.

Luca Pinello & Huidong Chen
MGH, HMS, Broad & MGH, HMS; Pinello Lab
Single-cell trajectory reconstruction, exploration and mapping from omics data

Abstract: Single-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell transcriptomic data, but efforts on analyzing single-cell epigenomic data and on trajectory visualization remain limited. Here we present STREAM, an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data. First, Luca Pinello will set the stage presenting the basic concepts of how to build a trajectory inference approach from scratch (a cookbook perspective). Then Huidong Chen will describe the method behind STREAM - a novel Elastic Principal Graph implementation (ElPiGraph), followed by a detailed discussion of how to visualize the learned trajectory and how to discover branch-specific genes, or genes differentiating between trajectory branches. We will close off with examining what we have learned so far and what the future directions and challenges are.