ArticleBioinformatics (Oxford, England)2022
SCAFE: a software suite for analysis of transcribed cis-regulatory elements in single cells.
Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- Accurate profiling of single-cell alternative transcript start sites by correcting RNA degradation.Nature communications · 2026Article
- So Fragile, So Human: Noncoding DNA Regions Orchestrating Gene Expression Involved in Neurodevelopmental Disorders and in Human Brain Evolution.International journal of molecular sciences · 2026Review
- Systematic evaluation of single-cell multimodal data integration enhances cell type resolution and discovery of clinically relevant states in complex tissues.Genome biology · 2026Article
- Estrogen signaling in PDGFRα+ cells positively regulates cortical bone metabolism via IGFBP5 in female mice.JBMR plus · 2026Article
- Defining the Cis-Regulatory Elements of SCN1A in GABAergic Interneurons.Molecular neurobiology · 2025Article
- Systematic evaluation of single-cell multimodal data integration for comprehensive human reference atlas.bioRxiv : the preprint server for biology · 2025Article
- Cell type-dependent directional transcription at enhancers.NAR genomics and bioinformatics · 2025Article
- Predicting and comparing transcription start sites in single cell populations.PLoS computational biology · 2025Article
- CamoTSS: analysis of alternative transcription start sites for cellular phenotypes and regulatory patterns from 5' scRNA-seq data.Nature communications · 2023Article
- ZENBU-Reports: a graphical web-portal builder for interactive visualization and dissemination of genome-scale data.NAR genomics and bioinformatics · 2023Article
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Authors and funding
7 authors.
Funding
Abstract
motivationCell 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.
resultsWe 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.
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