Data visualization software tools | Genome-wide association study data analysis
Genome-wide association studies (GWAS) are an important tool for the mapping of complex traits and diseases. Visual inspection of genomic annotations may be used to generate insights into the biological mechanisms underlying GWAS-identified loci.
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.
Enables tightly integrated comparative variant analysis and visualization of thousands of next generation sequencing (NGS) data samples and millions of variants. BasePlayer is a highly efficient and user-friendly software for biological discovery in large-scale NGS data. It transforms an ordinary desktop computer into a large-scale genomic research platform, enabling also a non-technical user to perform complex comparative variant analyses, population frequency filtering and genome level annotations under intuitive, scalable and highly-responsive user interface to facilitate everyday genetic research as well as the search of novel discoveries.
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.
Performs Principal Component Analysis (PCA) on 1 million individuals faster than competing approaches. FlashPCA uses bounded memory and maintains high accuracy for the top eigenvalues/eigenvectors. FlashPCA enables scalable and accurate PCA of large genotype datasets, using small amounts of memory, making it feasible to run such analyses on a standard personal computer, all within the R environment.
A tool to plot regional association results from genome-wide association scans or candidate gene studies. LocusZoom visually displays regional information such as the strength and extent of the association signal relative to genomic position, local linkage disequilibrium (LD) and recombination patterns and the positions of genes in the region.
Permits the exploration of patterns among tumor samples arranged relative to one another based on their molecular similarities. TumorMap consists of an analysis and visualization web portal that presents samples on the basis of their molecular profile similarity and attributes associated with samples, such as disease histological subtypes. Furthermore, this platform allows users to build their own interactive maps from several uploaded high-throughput platforms.
Allows users to perform visualization and clustering. SGTM was designed using the generative topographic mapping (GTM) algorithm. It consists of a modified nonlinear method aiming to diminish the dimension of X-variables and transform data points from the original space to the latent space. This tool changes the weight of each grid point, similar to the clustering of Gaussian mixture models (GMMs).
Simplifies interactive browsing of whole-genome association study results. GWAS GUI constructs graphical overviews of the results of whole-genome association studies (GWAS). It is useful for datasets with rich multi-dimensional phenotypic information, such as global surveys of gene expression. This tool was designed to ease data sharing within collaborative groups.
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.
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.
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.
An R package that enables enhanced data analysis and visualisation of results from GWAS. The package contains several utilities and modules that complement and enhance the functionality of the existing software. It also provides several tools for advanced visualisation of genomic data and utilises the power of the R language to aid in preparation of publication-quality figures. Some of the package functions are specific for the domestic dog (Canis familiaris) data.
A python package for viewing and exploring GWAS results not only using classic static Manhattan and quantile-quantile plots, but also through a dynamic extension which allows to visualize data interactively, and to visualize the relationships between GWAS results from multiple cohorts or studies. Assocplots makes it possible to browse multiple charts in real-time to better understand the relationships among groups.
Identifies risk variants for complex traits through a joint analysis of multiple Genome-Wide Association Studies (GWAS) datasets by leveraging pleiotropy. graph-GPA integrates a large number of GWAS datasets for multiple phenotypes using a hidden Markov random field approach. It promotes better understanding of genetic mechanisms shared among phenotypes, which can potentially be useful for the development of improved diagnosis and therapeutics.
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.
Allows users to capture the space variation of signals from a picture. FPCA permits an accurate feature selection in image clustering analysis using both spatial and spectral information. This tool uses four components: i) it uses high dimensional FPCA as a feature extraction technique; ii) it includes a theoretically provable accurate randomized feature selection algorithm; iii) it combines feature selection and feature extraction for dimensionality reduction, and iv) it uses spectral clustering with low rank matrix decomposition.
Inspects the pleiotropic architecture of genome-wide association studies (GWAS) datasets via an interactive and dynamic visualization tool. ShinyGPA provides a joint association mapping functionality that facilitates biological understanding of the pleiotropic architecture. This software uses the genetic analysis incorporating pleiotropy and annotation (GPA) model to estimate the pleiotropy for each pair of phenotypes.
A set of graphical tools for instant global and local viewing and graphing of GWAS results for all chromosomes and for each trait. The SNPEVG package is a versatile, flexible and efficient graphical tool for rapid digestion of large quantities of GWAS results with mouse clicks.
Provides a straightforward way to visually examine the large quantities of data collected through the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium. EnigmaVis is an intuitive tool allowing users to visualize and navigate through ENIGMA datasets by generating interactive plots. This approach enables interactive interrogating capabilities, tightly coupling the data to analysis and facilitating discovery.
An interactive GWAS viewer focused on comparing results across traits and other variables. Zbrowse can easily be run on a desktop computer with software that bioinformaticians are likely already familiar with. Additionally, the software can be hosted or embedded on a server for easy access by anyone with a modern web browser.