Please note, the input file should not contain the following column names : "seqnames", "ranges", "strand", "seqlevels", "seqlengths", "isCircular", "start", "end", "width", "element".
AnnotationsSelect the annotations you want to apply on your matrix.
These annotations are coming from UCSC Table Browser.
You can download the wanted annotations through the UCSC Table Browser HERE (select 'bed format' for positional annotations or 'data points' for quantitative annotations) or use your own annotation files. (200Mo max.)
These frequencies have been calculated by VEP (see 'Effect Prediction panel for more information') from 1000 Genomes Project Phase 3
Compute LD score with 1000Genomes data (phase 3). It may take several minutes depending on the number of variants in your query and their distance.
The VEP determines the effect of your variants on genes, transcripts, and protein sequence, as well as regulatory regions.
RegulomeDB is a database that annotates SNPs with known and redicted regulatory elements in the intergenic regions of the H. sapiens genome. Known and predicted regulatory DNA elements include regions of DNAase hypersensitivity, binding sites of factors, and promoter regions that have been biochemically characterized to regulation transcription. Source of these data include public datasets from GEO, the ENCODE project, and published literature.
HaploReg is a tool for exploring annotations of the noncoding genome at variants on haplotype blocks, such as candidate regulatory SNPs.
CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions variants in the human genome.Combined Annotation Dependent Depletion (CADD) is a framework that integrates multiple annotations into one metric by contrasting variants that survived natural selection with simulated mutations.
This section enables to compute a local scoring for each variant of your region. The weights can be chosen arbitrary or can be based on enrichissement results coming from prediction algorithms like PAINTOR (See below). You can manually weigthed the features and change the thresholds.
Please note that the heatmap contains only the 1000 first variants
fastPAINTOR (Probabilistic Annotation INtegraTOR), a probabilistic framework that integrates association strength with genomic functional annotation data to improve accuracy in selecting plausible causal variants for functional validation.The main output of PAINTOR are probabilities for every variant to be causal that can be used for prioritization in functional assays to establisb biological causality.
More information here .
fGWAS is a command line tool for integrating functional genomic information into a genome-wide association study (GWAS).
More information here .
A lot of other arguments enable to modify gwas behavior. You can add your tuning parameters as described fgwas user manual. For example, write '-k 1000' in the following box to change the number of SNPs in a region (default 5000)
CAVIAR-BF, a bayesian framework that incorporates genomic functional annotations dfor fine-mapping of causal variants.
In the present interface, we decided to use CAVIAR-BF with for the most part default settings. The details can be found in our User Manual.
More information here .
Correlations between genotype and tissue-specific gene expression levels will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx will help researchers to understand inherited susceptibility to disease and will be a resource database and tissue bank for many studies in the future.
VEXOR is a platform-independent browser-based integrative environment for functional annotation in R, based on the Shiny package. This interface provides a comprehensive analytical framework to characterize the role of variants driving susceptibility signals in regions defined by GWAS.
The matrix is connected to 1) publicly available functional annotations through UCSC and Ensembl Browsers, 2) genetic diversity information (1000 Genomes third phase MAF, Linkage Disequilibrium) 3) effect prediction tools (VEP, HaploReg), 4) functional scoring tools (CADD, RegulomeDB) 5) prioritization algorithm (PAINTOR), 6) pathway information (GeneMANIA) 7) regulation data (Enhancers, Super-enhancers, IM-PET, Chromatine states) and finally 8) relevant experimental data such as chromosomal interactions (Hi-C, 3C, 5C, ChIA-PET) and expression data (GTex).
Thus, the user is provided with a proximal and distal context for each variant to assist in the prediction of putative functional effects. VEXOR is a versatile and scalable tool designed to help the understanding of the functional context in fine-mapping analyses of complex traits.
How to cite
To cite the tool, please refer to : Audrey Lemaçon, Charles Joly Beauparlant, Penny Soucy, Jamie Allen, Douglas Easton, Peter Kraft, Jacques Simard, Arnaud Droit; VEXOR: an integrative environment for prioritization of functional variants in fine-mapping analysis. Bioinformatics 2016 btw826. doi: 10.1093/bioinformatics/btw826