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SCAFE: a software suite for analysis of transcribed cis-regulatory elements in single cells.
- Source :
-
Bioinformatics (Oxford, England) [Bioinformatics] 2022 Nov 15; Vol. 38 (22), pp. 5126-5128. - Publication Year :
- 2022
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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.)
- Subjects :
- Workflow
Transcription Initiation Site
Software
Regulatory Sequences, Nucleic Acid
Subjects
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