Samuel A Lambert1, Mihai Albu2, Timothy R Hughes1,2,3, Hamed S Najafabadi4,5. 1. Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada. 2. Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S 3E1, Canada. 3. Canadian Institutes for Advanced Research, Toronto, ON M5G 1Z8, Canada. 4. McGill University and Génome Québec Innovation Centre, Montreal, QC H3A 0G1, Canada. 5. Department of Human Genetics, McGill University, Montreal, QC H3A 1B1, Canada.
Abstract
Measuring motif similarity is essential for identifying functionally related transcription factors (TFs) and RNA-binding proteins, and for annotating de novo motifs. Here, we describe Motif Similarity Based on Affinity of Targets (MoSBAT), an approach for measuring the similarity of motifs by computing their affinity profiles across a large number of random sequences. We show that MoSBAT successfully associates de novo ChIP-seq motifs with their respective TFs, accurately identifies motifs that are obtained from the same TF in different in vitro assays, and quantitatively reflects the similarity of in vitro binding preferences for pairs of TFs. AVAILABILITY AND IMPLEMENTATION: MoSBAT is available as a webserver at mosbat.ccbr.utoronto.ca, and for download at github.com/csglab/MoSBAT. CONTACT: t.hughes@utoronto.ca or hamed.najafabadi@mcgill.caSupplementary information: Supplementary data are available at Bioinformatics online.
Measuring motif similarity is essential for identifying functionally related transcription factors (TFs) and RNA-binding proteins, and for annotating de novo motifs. Here, we describe Motif Similarity Based on Affinity of Targets (MoSBAT), an approach for measuring the similarity of motifs by computing their affinity profiles across a large number of random sequences. We show that MoSBAT successfully associates de novo ChIP-seq motifs with their respective TFs, accurately identifies motifs that are obtained from the same TF in different in vitro assays, and quantitatively reflects the similarity of in vitro binding preferences for pairs of TFs. AVAILABILITY AND IMPLEMENTATION: MoSBAT is available as a webserver at mosbat.ccbr.utoronto.ca, and for download at github.com/csglab/MoSBAT. CONTACT: t.hughes@utoronto.ca or hamed.najafabadi@mcgill.caSupplementary information: Supplementary data are available at Bioinformatics online.
Authors: Hamed S Najafabadi; Sanie Mnaimneh; Frank W Schmitges; Michael Garton; Kathy N Lam; Ally Yang; Mihai Albu; Matthew T Weirauch; Ernest Radovani; Philip M Kim; Jack Greenblatt; Brendan J Frey; Timothy R Hughes Journal: Nat Biotechnol Date: 2015-02-18 Impact factor: 54.908
Authors: Matthew T Weirauch; Ally Yang; Mihai Albu; Atina G Cote; Alejandro Montenegro-Montero; Philipp Drewe; Hamed S Najafabadi; Samuel A Lambert; Ishminder Mann; Kate Cook; Hong Zheng; Alejandra Goity; Harm van Bakel; Jean-Claude Lozano; Mary Galli; Mathew G Lewsey; Eryong Huang; Tuhin Mukherjee; Xiaoting Chen; John S Reece-Hoyes; Sridhar Govindarajan; Gad Shaulsky; Albertha J M Walhout; François-Yves Bouget; Gunnar Ratsch; Luis F Larrondo; Joseph R Ecker; Timothy R Hughes Journal: Cell Date: 2014-09-11 Impact factor: 41.582
Authors: April L Mueller; Carles Corbi-Verge; David O Giganti; David M Ichikawa; Jeffrey M Spencer; Mark MacRae; Michael Garton; Philip M Kim; Marcus B Noyes Journal: Nucleic Acids Res Date: 2020-06-19 Impact factor: 16.971
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