1 - 28 of 28 results

DANCE / Disease-ANCEstry Networks

A graph-based web tool that allows to integrate and visualize information on human complex phenotypes and their GWAS-hits, as well as their risk allele frequencies in different populations. DANCE integrates information from two existing databases: (i) GWAS-hit SNPs reported in the NHGRI-EBI GWAS Catalog and (ii) risk-allele frequencies in Europeans, Africans and Asians from the 1KGP. DANCE provides an interactive way to explore the human SNP-Disease Network and its projection, a Disease-Disease Network. With these functionalities, DANCE fills a gap in our ability to handle and understand the knowledge generated by GWAS and the 1000 Genomes Project.


A suite of JAVA software tools that provides a user-friendly interface to annotate, visualize, and help interpret the set of P-values emerging from a whole genome association (WGA) study. WGAViewer connects to the latest online genomic databases to annotate the SNPs and their associated P-values in the context of predicted gene structure and SNP function, association with gene expression, evidence of recent selection, and concurrent evidence from multiple association studies.


Visualizes genotype cluster plots designed to be integrated into quality control workflows for Genome-wide association studies (GWAS). Evoker provides a wide range of functionalities such as calling plots for particular markers or viewing a set of single nucleotide polymorphisms (SNPs) showing evidence for association. The software also allows users to visualize the effect triggers by excluding specific samples, and view multiple collections side by side to compare genotype calls across sample sets.


A tool that systematically supports genetic variant representation, annotation and prioritization for data generated from GWAS and NGS. GWASrap utilizes state-of-the-art web technologies to maximize user interaction and visualization of the results. For a given SNP dataset with its P-values, GWASrap will first provide a Circos-style plot to visualize any genetic variants at either the genome or chromosome level. The tool then combines different genomic features (SNP/CNV density, disease susceptibility loci, etc.) with comprehensive annotations that give the researcher an intuitive view of the functional significance of the different genomic regions.


A data visualisation and exploration tool for genetic association data. LocusExplorer is written in R using the Shiny library, providing access to powerful R-based functions through a simple user interface. LocusExplorer is designed to visualise multiple and diverse forms of genomic information, as individual tracks are aligned to a common genomic coordinate axis. Plot features and parameters can be adjusted dynamically throughout the plotting process. Publication quality finalized plots can be downloaded in PDF, SVG, JPEG and TIFF file formats. The design of LocusExplorer emphasizes simplicity of use and the simultaneous display of diverse annotations as its primary aims.


Permits users to view and navigate phenotype/genotype association results. Toppar is a customizable database-driven browser for genetic wide association studies (GWAS) data. The repository allows integration and visualization of analyses generated across multiple platforms and methodologies. It combines a whole-genome overview of GWAS results with an interactive regional display for loci of interest. Toppar enables comparison across multiple traits, using different tests and filters.


Allows visualization of large-scale genetic and genomic data exemplified by results from genome-wide association studies (GWAS). AssociationViewer provides an integrated framework to facilitate the interpretation of single nucleotide polymorphism (SNP) association studies in genomic context. It integrates functionalities that enable the aggregation or intersection of data tracks. The tool implements an efficient cache system and allows the display of several, very large-scale genomic datasets.


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.


An interactive analytics software platform that 1) automates the execution of principled machine learning methods that detect genome- and phenome-wide associations among genotypes, gene expression data, and clinical or other macroscopic traits, and 2) provides new visualization tools specifically designed to aid in the exploration of association mapping results. Algorithmically, GenAMap is based on a new paradigm for GWAS and PheWAS analysis, termed structured association mapping, which leverages various structures in the omic data.


A visualization tool that is specifically designed to analyze and explore genetic interactions. EINVis displays interactions among genetic markers as a network. EINVis utilizes a circular layout (specially, a tree ring view) to simultaneously visualize the hierarchical interactions between single nucleotide polymorphisms (SNPs), genes, and chromosomes, and the network structure formed by these interactions. Using EINVis, the user can distinguish marginal effects from interactions, track interactions involving more than two markers, visualize interactions at different levels, and detect proxy SNPs based on linkage disequilibrium. EINVis is an effective and user-friendly free visualization tool for analyzing and exploring genetic interactions.

MAVEN / Management, Analysis, Visualization and rEsults sharing

Allows users to visualize Genome-wide association studies (GWAS) results. MAVEN provides four main functionalities: (i) it accepts and stores GWAS results based on single-locus analysis methods, not the raw data; (ii) it offers several types of filtering capabilities for retrieving single nucleotide polymorphisms (SNPs) and gene regions; (iii) it displays search results in a tabular format and/or a graphical format; and (iv) it provides a functional annotation of a selected SNP from the result table. Furthermore, the software is not restricted to a single phenotype or single statistics.