SCAFE: a software suite for analysis of transcribed cis-regulatory elements in single cells

Abstract

Motivation: Cell type-specific activities of cis-regulatory elements (CRE) are central to understanding gene regulation and disease predisposition. Single-cell RNA 5'end sequencing (sc-end5-seq) captures the transcription start sites (TSS) which can be used as a proxy to measure the activity of transcribed CREs (tCREs). However, a substantial fraction of TSS identified from sc-end5-seq data may not be genuine due to various artifacts, hindering the use of sc-end5-seq for de novo discovery of tCREs.

Results: We developed SCAFE-Single-Cell Analysis of Five-prime Ends-a software suite that processes sc-end5-seq data to de novo identify TSS clusters based on multiple logistic regression. It annotates tCREs based on the identified TSS clusters and generates a tCRE-by-cell count matrix for downstream analyses. The software suite consists of a set of flexible tools that could either be run independently or as pre-configured workflows.

Availability and implementation: SCAFE is implemented in Perl and R. The source code and documentation are freely available for download under the MIT License from https://github.com/chung-lab/SCAFE. Docker images are available from https://hub.docker.com/r/cchon/scafe. The submitted software version and test data are archived at https://doi.org/10.5281/zenodo.7023163 and https://doi.org/10.5281/zenodo.7024060, respectively.

Supplementary information: Supplementary data are available at Bioinformatics online.

Fig. 1.

De novo identification of genuine TSS. (a) Distribution of TSS clusters properties (left) and their classification performances measured as AUC (right). (b) Distribution of probability (TSS classifier) (left) and its classification performance measured as AUC (right). (c) Performance of various metrics as a TSS classifier in (a) and (b) across various sequencing depths. (d) Histone marks at TSS clusters with a probability below (left) or above (right) 0.5 cutoff, at annotated gene TSS, exonic or intronic regions in sense or antisense orientations, or otherwise intergenic regions. n, number of TSS clusters; %, percentage of TSS clusters in all genomic locations regardless of probability thresholds