ArticleBMC genomics2014
Improving analysis of transcription factor binding sites within ChIP-Seq data based on topological motif enrichment.
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Nonconsensus flanking sequence of hundreds of base pairs around in vivo binding sites: statistical beacons for transcription factor scanning.Nucleic acids research · 2026Article
- An epigenomic investigation of atrial fibrillation in a matched left and right atrial human cohort.Clinical epigenetics · 2026Article
- Benchmarking transcription factor binding site prediction models: a comparative analysis on synthetic and biological data.Briefings in bioinformatics · 2025Article
- Single-cell chromatin accessibility reveals malignant regulatory programs in primary human cancers.Science (New York, N.Y.) · 2024Article
- Genomic background sequences systematically outperform synthetic ones in de novo motif discovery for ChIP-seq data.NAR genomics and bioinformatics · 2024Article
- Regression convolutional neural network models implicate peripheral immune regulatory variants in the predisposition to Alzheimer's disease.PLoS computational biology · 2024Article
- TFscope: systematic analysis of the sequence features involved in the binding preferences of transcription factors.Genome biology · 2024Article
- Aberrant non-canonical NF-κB signalling reprograms the epigenome landscape to drive oncogenic transcriptomes in multiple myeloma.Nature communications · 2024Article
- Peak Scores Significantly Depend on the Relationships between Contextual Signals in ChIP-Seq Peaks.International journal of molecular sciences · 2024Article
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- Motif models proposing independent and interdependent impacts of nucleotides are related to high and low affinity transcription factor binding sites in Arabidopsis.Frontiers in plant science · 2022Article
- Addiction-Associated Genetic Variants Implicate Brain Cell Type- and Region-Specific Cis-Regulatory Elements in Addiction Neurobiology.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
- Biologically relevant transfer learning improves transcription factor binding prediction.Genome biology · 2021Article
- BiasAway: command-line and web server to generate nucleotide composition-matched DNA background sequences.Bioinformatics (Oxford, England) · 2021Article
- Article
- MEIRLOP: improving score-based motif enrichment by incorporating sequence bias covariates.BMC bioinformatics · 2020Article
- Article
- Mechanistic insights into transcription factor cooperativity and its impact on protein-phenotype interactions.Nature communications · 2020Article
- Identification of Key Tissue-Specific, Biological Processes by Integrating Enhancer Information in Maize Gene Regulatory Networks.Frontiers in genetics · 2020Article
- Diverse families of transposable elements affect the transcriptional regulation of stress-response genes in Drosophila melanogaster.Nucleic acids research · 2019Article
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4 authors.
Funding
Abstract
backgroundChromatin immunoprecipitation (ChIP) coupled to high-throughput sequencing (ChIP-Seq) techniques can reveal DNA regions bound by transcription factors (TF). Analysis of the ChIP-Seq regions is now a central component in gene regulation studies. The need remains strong for methods to improve the interpretation of ChIP-Seq data and the study of specific TF binding sites (TFBS).
resultsWe introduce a set of methods to improve the interpretation of ChIP-Seq data, including the inference of mediating TFs based on TFBS motif over-representation analysis and the subsequent study of spatial distribution of TFBSs. TFBS over-representation analysis applied to ChIP-Seq data is used to detect which TFBSs arise more frequently than expected by chance. Visualization of over-representation analysis results with new composition-bias plots reveals systematic bias in over-representation scores. We introduce the BiasAway background generating software to resolve the problem. A heuristic procedure based on topological motif enrichment relative to the ChIP-Seq peaks' local maximums highlights peaks likely to be directly bound by a TF of interest. The results suggest that on average two-thirds of a ChIP-Seq dataset's peaks are bound by the ChIP'd TF; the origin of the remaining peaks remaining undetermined. Additional visualization methods allow for the study of both inter-TFBS spatial relationships and motif-flanking sequence properties, as demonstrated in case studies for TBP and ZNF143/THAP11.
conclusionsTopological properties of TFBS within ChIP-Seq datasets can be harnessed to better interpret regulatory sequences. Using GC content corrected TFBS over-representation analysis, combined with visualization techniques and analysis of the topological distribution of TFBS, we can distinguish peaks likely to be directly bound by a TF. The new methods will empower researchers for exploration of gene regulation and TF binding.
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