Abstract
Single-cell CRISPR screens are a promising biotechnology for mapping regulatory elements to target genes at genome-wide scale. However, technical factors like sequencing depth impact not only expression measurement but also perturbation detection, creating a confounding effect. We demonstrate on two single-cell CRISPR screens how these challenges cause calibration issues. We propose SCEPTRE: analysis of single-cell perturbation screens via conditional resampling, which infers associations between perturbations and expression by resampling the former according to a working model for perturbation detection probability in each cell. SCEPTRE demonstrates very good calibration and sensitivity on CRISPR screen data, yielding hundreds of new regulatory relationships supported by orthogonal biological evidence.
Highlights
The noncoding genome plays a crucial role in human development and homeostasis: over 90% of loci implicated by GWAS in diseases lie in regions outside protein-coding exons [1]
In the “Discussion” section, we describe an independent work conducted in parallel to the current study in which we leveraged biobank-scale GWAS data, single-cell CRISPR screens, and SCEPTRE to dissect the cis and trans effects of noncoding variants associated with blood diseases [14]
Single-cell CRISPR screens will play a key role in unraveling the regulatory architecture of the noncoding genome [23]
Summary
The noncoding genome plays a crucial role in human development and homeostasis: over 90% of loci implicated by GWAS in diseases lie in regions outside protein-coding exons [1]. While millions of cisregulatory elements (CREs) have been nominated through biochemical annotations, the functional role of these CREs, including the genes that they target, remain essentially unknown [2]. A central challenge over the coming decade, is to unravel the cis-regulatory landscape of the genome across various cell types and diseases. Single-cell CRISPR screens (implemented by Perturb-seq [3, 4], CROP-seq [5], ECCITE-seq [6], and other protocols) are among the most promising technologies for mapping CREs to their target genes at genome-wide scale. High multiplicity of infection (MOI) screens deliver dozens perturbations to each cell [7,8,9], enabling the interrogation
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