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, 31 (23), 3847-9

motifbreakR: An R/Bioconductor Package for Predicting Variant Effects at Transcription Factor Binding Sites


motifbreakR: An R/Bioconductor Package for Predicting Variant Effects at Transcription Factor Binding Sites

Simon G Coetzee et al. Bioinformatics.


Functional annotation represents a key step toward the understanding and interpretation of germline and somatic variation as revealed by genome-wide association studies (GWAS) and The Cancer Genome Atlas (TCGA), respectively. GWAS have revealed numerous genetic risk variants residing in non-coding DNA associated with complex diseases. For sequences that lie within enhancers or promoters of transcription, it is not straightforward to assess the effects of variants on likely transcription factor binding sites. Consequently we introduce motifbreakR, which allows the biologist to judge whether the sequence surrounding a polymorphism or mutation is a good match, and how much information is gained or lost in one allele of the polymorphism or mutation relative to the other. MotifbreakR is flexible, giving a choice of algorithms for interrogation of genomes with motifs from many public sources that users can choose from. MotifbreakR can predict effects for novel or previously described variants in public databases, making it suitable for tasks beyond the scope of its original design. Lastly, it can be used to interrogate any genome curated within bioconductor.

Availability and implementation:,



Fig. 1.
Fig. 1.
Example of motifbreakR output from plotMB function for a previously published SNP (Hazelett et al., 2014). Genomic sequence and coordinates are at the bottom of the display; the positions of the matches represented (light blue boxes). The position of the SNP within the motif is indicated with red bounding box and alternate allele below, and as red text on the motif logo position bar above. The motif logos generated from motifstack are shown above using the color conventions of the genomic sequence below

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