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

Authors :
Moody J
Kouno T
Chang JC
Ando Y
Carninci P
Shin JW
Hon CC
Source :
Bioinformatics (Oxford, England) [Bioinformatics] 2022 Nov 15; Vol. 38 (22), pp. 5126-5128.
Publication Year :
2022

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.<br />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.<br />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.<br />Supplementary Information: Supplementary data are available at Bioinformatics online.<br /> (© The Author(s) 2022. Published by Oxford University Press.)

Details

Language :
English
ISSN :
1367-4811
Volume :
38
Issue :
22
Database :
MEDLINE
Journal :
Bioinformatics (Oxford, England)
Publication Type :
Academic Journal
Accession number :
36173306
Full Text :
https://doi.org/10.1093/bioinformatics/btac644