Genome-wide association studies revealed that most disease-associated single nucleotide polymorphisms (SNPs) are located in regulatory regions within introns or in regions between genes. Regulatory SNPs (rSNPs) are such SNPs that affect gene regulation by changing transcription factor (TF) binding affinities to genomic sequences. Identifying potential rSNPs is crucial for understanding disease mechanisms.
Provides a unified portal for online discovery and analysis of sequence motifs representing features such as DNA binding sites and protein interaction domains. The popular MEME motif discovery algorithm is now complemented by the GLAM2 algorithm which allows discovery of motifs containing gaps. Three sequence scanning algorithms--MAST, FIMO and GLAM2SCAN--allow scanning numerous DNA and protein sequence databases for motifs discovered by MEME and GLAM2. Transcription factor motifs (including those discovered using MEME) can be compared with motifs in many popular motif databases using the motif database scanning algorithm TOMTOM. Transcription factor motifs can be further analyzed for putative function by association with Gene Ontology (GO) terms using the motif-GO term association tool GOMO. MEME output now contains sequence LOGOS for each discovered motif, as well as buttons to allow motifs to be conveniently submitted to the sequence and motif database scanning algorithms (MAST, FIMO and TOMTOM), or to GOMO, for further analysis. GLAM2 output similarly contains buttons for further analysis using GLAM2SCAN and for rerunning GLAM2 with different parameters.
A tool for exploring annotations of the noncoding genome at variants on haplotype blocks, such as candidate regulatory SNPs at disease-associated loci. Using LD information from the 1000 Genomes Project, linked SNPs and small indels can be visualized along with chromatin state and protein binding annotation from the Roadmap Epigenomics and ENCODE projects, sequence conservation across mammals, the effect of SNPs on regulatory motifs, and the effect of SNPs on expression from eQTL studies. HaploReg is designed for researchers developing mechanistic hypotheses of the impact of non-coding variants on clinical phenotypes and normal variation.
Offers a platform dedicated to the investigation of single nucleotides polymorphisms (SNP) and indels involved into transcription factor binding (TFB) within the human genome. SNP2TFBS is composed of three main features : (i) SNPViewer to browse TFBS variability by rsID; (ii) SNSelect for annotating sets of SNPs and displaying statistics about binding sites frequencies and; (iii) PWMViewer which permits users to visualize models recorded in the repository.
A sequence-based computational method to predict the effect of regulatory variation, using a classifier (gkm-SVM) that encodes cell type-specific regulatory sequence vocabularies. The induced change in the gkm-SVM score, deltaSVM, quantifies the effect of variants. We show that deltaSVM accurately predicts the impact of SNPs on DNase I sensitivity in their native genomic contexts and accurately predicts the results of dense mutagenesis of several enhancers in reporter assays. deltaSVM provides a powerful computational approach to systematically identify functional regulatory variants.
Predicts whether a SNP is an rSNP. For a given SNP, and using a statistical framework, is-rSNP can successfully predict the set of TFs for which binding is affected. It provides the statistical power to scan large numbers of SNPs, making it suitable to use to screen all associated SNPs output by a typical GWAS.
An R package for predicting the disruptiveness of single nucleotide polymorphisms on transcription factor binding sites. motifbreakR 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.
Informs users on single nucleotide polymorphism (SNP)-related regulatory elements in human. rSNPBase provides annotation for SNPs including related regulatory elements and regulatory element-target gene pairs (E–G pairs). The tool is organized around two main features: a rSNP search and a network search that both provide information about the element gene pairs, extended annotations or related-elements on specific SNPs and SNP-related graphic networks.