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SCAFE: a software suite for analysis of transcribed cis-regulatory elements in single cells
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 tran...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9665856/ https://www.ncbi.nlm.nih.gov/pubmed/36173306 http://dx.doi.org/10.1093/bioinformatics/btac644 |
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author | Moody, Jonathan Kouno, Tsukasa Chang, Jen-Chien Ando, Yoshinari Carninci, Piero Shin, Jay W Hon, Chung-Chau |
author_facet | Moody, Jonathan Kouno, Tsukasa Chang, Jen-Chien Ando, Yoshinari Carninci, Piero Shin, Jay W Hon, Chung-Chau |
author_sort | Moody, Jonathan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9665856 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-96658562022-11-16 SCAFE: a software suite for analysis of transcribed cis-regulatory elements in single cells Moody, Jonathan Kouno, Tsukasa Chang, Jen-Chien Ando, Yoshinari Carninci, Piero Shin, Jay W Hon, Chung-Chau Bioinformatics Applications Note 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. Oxford University Press 2022-09-29 /pmc/articles/PMC9665856/ /pubmed/36173306 http://dx.doi.org/10.1093/bioinformatics/btac644 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Note Moody, Jonathan Kouno, Tsukasa Chang, Jen-Chien Ando, Yoshinari Carninci, Piero Shin, Jay W Hon, Chung-Chau SCAFE: a software suite for analysis of transcribed cis-regulatory elements in single cells |
title | SCAFE: a software suite for analysis of transcribed cis-regulatory elements in single cells |
title_full | SCAFE: a software suite for analysis of transcribed cis-regulatory elements in single cells |
title_fullStr | SCAFE: a software suite for analysis of transcribed cis-regulatory elements in single cells |
title_full_unstemmed | SCAFE: a software suite for analysis of transcribed cis-regulatory elements in single cells |
title_short | SCAFE: a software suite for analysis of transcribed cis-regulatory elements in single cells |
title_sort | scafe: a software suite for analysis of transcribed cis-regulatory elements in single cells |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9665856/ https://www.ncbi.nlm.nih.gov/pubmed/36173306 http://dx.doi.org/10.1093/bioinformatics/btac644 |
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