GenoCLAMP: consolidation of sequence motifs from genomic-scale data

Genome-wide protein–DNA mapping studies have produced thousands of enriched sequence motifs, many of which are redundant because transcription factors (TFs) bind cooperatively as distinct complexes to shared sites. Here, we present Genomic CLustered Alignment of Motif Profiles (GenoCLAMP), an algorithm that unifies motif-clustering and alignment to collapse redundant motifs into high-quality merged matrix representations. We demonstrate that GenoCLAMP reliably recovers known TF complexes that bind common motifs and uncovers evidence for previously uncharacterized motifs. These results establish GenoCLAMP as a robust and efficient framework for motif consolidation, enhancing computational analyses and biological interpretation of large-scale TF–DNA binding datasets.

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Publication Details

Journal
Genome biology
Published
2026-10-16
DOI
https://doi.org/10.1186/s13059-026-04283-9
Primary Topic
Genomics and Chromatin Dynamics
Type
article
Field-Weighted Citation Impact
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article

GenoCLAMP: consolidation of sequence motifs from genomic-scale data

William Lai, B. Franklin Pugh, Justin Sungsoo Cha
Genome biology
Genomics and Chromatin Dynamics
article

GenoCLAMP: consolidation of sequence motifs from genomic-scale data

William Lai, B. Franklin Pugh, Justin Sungsoo Cha
article en

Abstract

Genome-wide protein–DNA mapping studies have produced thousands of enriched sequence motifs, many of which are redundant because transcription factors (TFs) bind cooperatively as distinct complexes to shared sites. Here, we present Genomic CLustered Alignment of Motif Profiles (GenoCLAMP), an algorithm that unifies motif-clustering and alignment to collapse redundant motifs into high-quality merged matrix representations. We demonstrate that GenoCLAMP reliably recovers known TF complexes that bind common motifs and uncovers evidence for previously uncharacterized motifs. These results establish GenoCLAMP as a robust and efficient framework for motif consolidation, enhancing computational analyses and biological interpretation of large-scale TF–DNA binding datasets.

Genome biology
Cornell University (US), University at Buffalo, State University of New York (US)
Openalex Percentile: Top 23%
Genomics and Chromatin Dynamics
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