ArticleNucleic acids research2017
RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections.
Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 papers.
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84 citing papers in PubMed.
- Massively parallel assessment of gene regulatory activity at human cortical-structure-associated variants.Nature neuroscience · 2026Article
- Sequence-based modeling of low-affinity transcription factor-DNA binding through deep learning.NAR genomics and bioinformatics · 2026Article
- AmalgaMo: flexible DNA motif merging.Bioinformatics advances · 2026Article
- The Binding Landscape of an Essential Nuclear Hormone Receptor inbioRxiv : the preprint server for biology · 2025Article
- Decoding cell-class specific roles of non-coding variants in human retina.Scientific reports · 2025Article
- Massively parallel assay of human splice variants reveals cis-regulatory drivers of disease-associated and cell type-specific splicing regulation.bioRxiv : the preprint server for biology · 2025Article
- Temporal regulation of gene expression during auxin-triggered crown root formation in barley: an integrated approach.Plant & cell physiology · 2025Article
- A transcription factor ensemble orchestrates bundle sheath expression in rice.Nature communications · 2025Article
- Iterative deep learning design of human enhancers exploits condensed sequence grammar to achieve cell-type specificity.Cell systems · 2025Article
- NKX2-5 congenital heart disease mutations show diverse loss and gain of epigenomic, biochemical and chromatin search functions underpinning pathogenicity.bioRxiv : the preprint server for biology · 2025Article
- A transcription factor module mediating CEMBO reports · 2025Article
- Transcriptome analysis reveals a de novo DNA element that may interact with chromatin-associated proteins in Plasmodium berghei during erythrocytic development.Scientific reports · 2025Article
- The regulatory landscape of 5' UTRs in translational control during zebrafish embryogenesis.Developmental cell · 2025Article
- Multiplexed CRISPRi Reveals a Transcriptional Switch Between KLF Activators and Repressors in the Maturing Neocortex.bioRxiv : the preprint server for biology · 2025Article
- Transcriptional regulation of the piRNA pathway by Ovo in animal ovarian germ cells.Genes & development · 2025Article
- Regulation of meristem and hormone function revealed through analysis of directly-regulated SHOOT MERISTEMLESS target genes.Scientific reports · 2025Article
- Identifying transcription factors with cell-type specific DNA binding signatures.BMC genomics · 2024Article
- Identification of transcription factor co-binding patterns with non-negative matrix factorization.Nucleic acids research · 2024Article
- Article
- TFscope: systematic analysis of the sequence features involved in the binding preferences of transcription factors.Genome biology · 2024Article
24 more citing papers are in PubMed but not listed here.
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5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Transcription factor (TF) databases contain multitudes of binding motifs (TFBMs) from various sources, from which non-redundant collections are derived by manual curation. The advent of high-throughput methods stimulated the production of novel collections with increasing numbers of motifs. Meta-databases, built by merging these collections, contain redundant versions, because available tools are not suited to automatically identify and explore biologically relevant clusters among thousands of motifs. Motif discovery from genome-scale data sets (e.g. ChIP-seq) also produces redundant motifs, hampering the interpretation of results. We present matrix-clustering, a versatile tool that clusters similar TFBMs into multiple trees, and automatically creates non-redundant TFBM collections. A feature unique to matrix-clustering is its dynamic visualisation of aligned TFBMs, and its capability to simultaneously treat multiple collections from various sources. We demonstrate that matrix-clustering considerably simplifies the interpretation of combined results from multiple motif discovery tools, and highlights biologically relevant variations of similar motifs. We also ran a large-scale application to cluster ∼11 000 motifs from 24 entire databases, showing that matrix-clustering correctly groups motifs belonging to the same TF families, and drastically reduced motif redundancy. matrix-clustering is integrated within the RSAT suite (http://rsat.eu/), accessible through a user-friendly web interface or command-line for its integration in pipelines.
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