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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.

SPOT / SNP Prioritization Online Tool

A web site for integrating biological databases into the prioritization of single nucleotide polymorphisms (SNPs) for further study after a genome-wide association study (GWAS). Typically, the next step after a GWAS is to genotype the top signals in an independent replication sample. Investigators will often incorporate information from biological databases so that biologically relevant SNPs, such as those in genes related to the phenotype or with potentially non-neutral effects on gene expression such as a splice sites, are given higher priority.

VSE / Variant Set Enrichment

Calculates the enrichment of a set of disease-associated variants across functionally annotated genomic regions, consequently highlighting the mechanisms important in the etiology of the disease studied. VSE is a computational method that relies on the set of genetic predispositions and functional annotations. It renders the software applicable to the study of any genetically inherited disease for which these data are available. VSE computes a network of all single nucleotide polymorphisms (SNPs) in which each SNP is represented as a node and the pairwise linkage disequilibrium (LD) as an edge.


Prioritizes the protein-coding part of the human genome to shortlist candidate genes for targeted follow-up studies. MetaRanker 2.0 allows user to upload lists of genes and their scores, which can denote tissue-specific expression levels. It facilitates prioritization of genes based on user-specified genome-wide association (GWA) summary statistics. The web server can also be used to rank genes based on their gene products’ propensity. This tool permits user to upload a larger number of phenotype specific data sets.


Uses enrichment of genome-wide association summary statistics to identify trait-relevant cellular functional annotations. RolyPoly is a regression-based polygenic model that can prioritize trait-relevant cell types and genes. This package is meant to identify enrichment of single nucleotide polymorphism (SNP)-trait association signal in functional annotations. Additionally, it computes a trait-relevance score for each gene which reflects the importance of expression specific to a cell type.


Detects novel gene-disease associations in humans. PhenoPred is based on an experimental protein-protein interaction (PPI) network, protein-disease associations, as well as protein sequence and functional annotation. It prioritizes genes based on their likelihood to be associated with a given disease or can prioritize diseases for a given query gene. The tool organizes disease terms into a hierarchical structure expanding from the “disease” term to the most specific disease names in a top-down manner, by using Disease Ontology (DO) information.


Enables the identification of candidate functional SNPs by integrating information from tagSNP locations, lists of linked SNPs from the 1000 genomes project and locations of chromatin features which may have functional significance. FunciSNP aids in the identification of candidate functional SNPs associated with a phenotype by integrating and correlating knowledge obtained from three whole-genome sequencing data types (1000 genomes, GWAS SNPs and sequence-based chromatin maps). Integrating non-coding regions as annotated by chromatin mapping helps inform and prioritize candidate regulatory regions for follow up molecular experiments.

iGWAS / integrative Genome-Wide Association Studies

Analyzes multiplatform genomic data under the family-based design. The iGWAS approach is developed within the framework of causal mediation modeling using counterfactuals. It considers the coordinated biological process from genetics to gene transcription and then to disease outcome. It also facilitates the study of mediation effect (eQTL genetic effect on a phenotype mediated through gene expression) and the alternative effect (genetic effect through other biological pathways or environment-mediated mechanisms), and incorporates the family design.


A command line tool for integrating functional genomic information into a genome-wide association study (GWAS). The basic setup is as follows: you have performed a GWAS or a meta-analysis of many GWAS, and have identified tens of loci that influence the disease or trait (our approach works best if there are at least ~20 independent loci with p-values less than 5e-8). We set out to address the following questions: (i) Are these associations enriched in particular types of regions of the genome (coding exons, DNAse hypersensitive sites, etc.)?, and (ii) Can we use these enrichments (if they exist) to identify novel loci influencing the trait?


Allows detection of individual regulatory single nucleotide polymorphisms (SNPs) from genotypes. DeepWAS proceeds to identification of individual regulatory SNPs by investigating genomic location and sequence alterations. It also identifies single deepSNPs with predicted allele-specific regulatory effect in a function unit, a cell-type and chromatin feature. This tool includes putative regulatory mechanisms in the genome-wide association study (GWAS) analysis from the start. It can control false discovery error by reducing multiple testing.


Allows users to search polymorphic markers in specified regions and/or motifs genome-wide. ReMo-SNPs can analyze genome-wide data and combine input from in silico and in vitro analyses. The software allows users to search for single nucleotide polymorphisms (SNPs) in both regions and motifs of interest, which enables combination of in silico identified motif data with functional in vitro or in vivo experimental data. It can be used to enrich genetic data sets for predicted functional variants.

FUMA / Functional Mapping and Annotation

Provides an easy-to-use tool to functionally annotate, visualize, and interprets results from genetic association studies and to quickly gain insight into the directional biological implications of significant genetic associations. FUMA combines information of state-of-the-art biological data sources in a single platform to facilitate the generation of hypotheses for functional follow-up analysis aimed at proving causal relations between genetic variants and diseases.


Facilitates the comparison of any two sets of genome alignments for the purpose of rapidly identifying the spectrum of nonsynonymous changes, insertions or deletions. MinoritReport also copies number variations in a presumed mutant relative to its parent. It relates mapped sequence reads in SAM format output from any alignment tool for both the mutant and parent genome, relative to a reference genome, and produces the set of variants that distinguishes the mutant from the parent, all presented in an intuitive, straightforward report format.

GARFIELD / GWAS Analysis of Regulatory or Functional Information Enrichment with LD correction

Leverages GWAS findings with regulatory or functional annotations to find features relevant to a phenotype of interest. GARFIELD analyses the enrichment patterns of publicly available GWAS summary statistics using regulatory maps from the ENCODE and Roadmap Epigenomics projects. This tool illustrates the molecular and cellular basis of well-studied traits, and helps drive novel biological insights and enhance efforts to robustly prioritise variants for follow-up studies across existing and future association studies.


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.


An interactive web-based SNP analysis tool that allows for the selection of relevant SNPs within a gene, based on different characteristics of the SNP itself, such as validation status, type, frequency/population data and putative functional properties (pathological SNPs, SNPs disrupting potential transcription factor binding sites, intron/exon boundaries...). Also, PupaSuite provides information about LD parameters (based on genotype data from HapMap) and identifies haplotype blocks and tag SNPs (using the Haploview software).


An unsupervised learning framework to predict tissue-specific functional regions through integrating high-throughput epigenomic annotations. GenoSkyline successfully identified a variety of non-coding regulatory machinery including enhancers, regulatory miRNA, and hypomethylated transposable elements in extensive case studies. Integrative analysis of GenoSkyline annotations and a collection of genome-wide association studies showed novel biological insight of human complex traits. In summary, GenoSkyline annotations can guide genetic studies at multiple resolutions and provide valuable insights in understanding complex diseases.

GKnowMTest / Genomic Knowledge-guided Multiple Testing

Provides a statistical framework for pathway-guided genome-wide analysis studies (GWAS). GKnowMTest is a package that proposes various methods with the aim of enabling routine use of pathway and other annotations for re-weighted analysis of GWAS. It is composed of different steps including (i) an enrichment estimation; (ii) a PMLR (Posterior Marginal Logistic Regression) method; and (iii) a prioritized testing. This approach can be applied for different priors such as single nucleotides polymorphisms (SNP)-level functional annotations.


Allows exploration of genome-wide association studies (GWAS) association results. LDassoc is a web module, in the LDlink suite of web tools, allowing users to upload and visualize GWAS association results, merge this results with data on linkage disequilibrium (LD), minor allele frequency (MAF) frequency, variant regulatory potential, and neighboring genes, (4) filter and sort them in interactive tables and (5) export them to the University of California Santa Cruz (UCSC) Genome Browser for further integration with data tracks.