ArticleNucleic acids research2013
Wellington: a novel method for the accurate identification of digital genomic footprints from DNase-seq data.
Article in Nucleic acids research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 137 papers.
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137 citing papers in PubMed, 223 citations in OpenAlex.
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- Comparative Profiling of Regulatory Modules as a Tool for Identifying the Transcription Factor Network Linked to Leukemogenesis.Methods in molecular biology (Clifton, N.J.) · 2025Article
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- Characterization of the DNA accessibility of chloroplast genomes in grasses.Communications biology · 2024Article
- Uncovering uncharacterized binding of transcription factors from ATAC-seq footprinting data.Scientific reports · 2024Article
- Integrative high-throughput enhancer surveying and functional verification divulges a YY2-condensed regulatory axis conferring risk for osteoporosis.Cell genomics · 2024Article
- Gene regulatory network analysis predicts cooperating transcription factor regulons required for FLT3-ITD+ AML growth.Cell reports · 2023Article
- Neuronal transcription of autism gene PTCHD1 is regulated by a conserved downstream enhancer sequence.Scientific reports · 2023Article
- Transcriptional reprogramming by mutated IRF4 in lymphoma.Nature communications · 2023Article
- Integrated 3D genome, epigenome and transcriptome analyses reveal transcriptional coordination of circadian rhythm in rice.Nucleic acids research · 2023Article
- Dictys: dynamic gene regulatory network dissects developmental continuum with single-cell multiomics.Nature methods · 2023Article
- High-throughput functional dissection of noncoding SNPs with biased allelic enhancer activity for insulin resistance-relevant phenotypes.American journal of human genetics · 2023Article
- RGT: a toolbox for the integrative analysis of high throughput regulatory genomics data.BMC bioinformatics · 2023Article
- Epigenetic and transcriptional regulations prime cell fate before division during human pluripotent stem cell differentiation.Nature communications · 2023Article
- Osteocyte Egln1/Phd2 links oxygen sensing and biomineralization via FGF23.Bone research · 2023Article
77 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
The expression of eukaryotic genes is regulated by cis-regulatory elements such as promoters and enhancers, which bind sequence-specific DNA-binding proteins. One of the great challenges in the gene regulation field is to characterise these elements. This involves the identification of transcription factor (TF) binding sites within regulatory elements that are occupied in a defined regulatory context. Digestion with DNase and the subsequent analysis of regions protected from cleavage (DNase footprinting) has for many years been used to identify specific binding sites occupied by TFs at individual cis-elements with high resolution. This methodology has recently been adapted for high-throughput sequencing (DNase-seq). In this study, we describe an imbalance in the DNA strand-specific alignment information of DNase-seq data surrounding protein-DNA interactions that allows accurate prediction of occupied TF binding sites. Our study introduces a novel algorithm, Wellington, which considers the imbalance in this strand-specific information to efficiently identify DNA footprints. This algorithm significantly enhances specificity by reducing the proportion of false positives and requires significantly fewer predictions than previously reported methods to recapitulate an equal amount of ChIP-seq data. We also provide an open-source software package, pyDNase, which implements the Wellington algorithm to interface with DNase-seq data and expedite analyses.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.