The application will not store or share any uploaded or analysed data on the server.
HADA input can be provided in different ways for annotation process:
It is not allowed to upload or analyse multisample VCF files.
HADA is designed for annotate VCF and plot pathogenicity results in Shiny R package for reported variation in Hereditary Angioedema (hereinafter namely as HAE).
HADA input can be provided in different ways for annotation process:
A reference of input formats is provided at input page by clicking in “example_variants”, allowing a preview use of HADA to users.
Note: In case of a VCF will be selected as input, only related variation with Hereditary Angioedema will be provided to users.
HADA integrates information of pathogenicity predictors such as SIFT, POLYPHEN2, LRT, METASVM, etc. for reported variation in Hereditary Angioedema. Through literature revision and databases exploration, causal variation is registered in HADA database, allowing to users a fast way to detect and analyse genetic variation related to HAE.
ExAC: A database that incorpores allele frequency calculation by 60,706 individuals sequenced in different genetic studies. This dataset serves as a reference set of allele frequencies for disease studies. ExAC provides frequencies for several human populations.
gnomAD: The Genome Aggregation Database (gnomAD) is a resource developed by an international coalition of investigators, with the goal of aggregating and harmonizing both exome and genome sequencing data from a wide variety of large-scale sequencing projects and making summary data available for the wider scientific community. The data set provided on this website spans 125,748 exome sequences and 15,708 whole-genome sequences from unrelated individuals sequenced as part of various disease-specific and population genetic studies.
SIFT: SIFT predicts whether an amino acid substitution affects protein function based on sequence homology and the physical properties of amino acids. It was build for missense deleteriousness prediction.
Polyphen2: PolyPhen-2 (Polymorphism Phenotyping v2) is a tool for possible impact prediction of amino acid substitutions on the structure and function of human protein using straightforward physical and comparative considerations.
MutationTaster2: Evaluates the pathogenic potential of DNA sequence alterations. It is designed to predict the functional consequences of not only amino acid substitutions but also intronic and synonymous alterations, short insertion and/or deletion (indel) mutations and variants spanning intron-exon borders.
Combined Annotation Dependent Depletion (CADD): CADD is a tool for scoring the deleteriousness of single nucleotide variants as well as insertion/deletions variants in the human genome. It integrates multiple annotations into one metric by contrasting variants that survived natural selection with simulated mutations.
Likelihood Ratio Test (LRT): The likelihood ratio test (LRT) is a statistical test of the goodness-of-fit between two models. A relatively more complex model is compared to a simpler model to see if it fits a particular dataset significantly better. If so, the additional parameters of the more complex model are often used in subsequent analyses. The LRT is only valid if used to compare hierarchically nested models.
MetaSVM: Achieves the purpose of meta-analysis as jointly leveraging multiple omics data. Meta-SVM is a meta-analytic support vector machine (SVM) that can accommodate multiple omics data, making it possible to detect consensus genes associated with diseases across studies. The objective function of Meta-SVM applies the hinge loss and the sparse group lasso. It also facilitates identifying potential biomarkers and elucidating the disease process.
PON-P2: PON-P2 is a random forest predictor for pathogenicity-association of amino acid substitutions. PON-P2 makes predictions only for variations leading to amino acid substitutions.
Users can plot the results by histograms or pie graphs with pathogenicity scores or ACMG class. For its representation, users need to select the score in gene plot tab. Users can generate a combined representation of ACMG classes using the information provided by ClinVar, Intervar and Varsome, allowing the benchmark the differences in pathogenicity classification for the same variant and all submitted variation.
HADA annotation results can be downloaded after processing steps in different format files such as text file (.txt), comma separated values (.csv), tab separated values (.tsv) or variant calling file (.VCF) with the pathogenicity information for each detected variant. If a VCF format is selected for downloading, users can choose a short file describing only HAE variants detected or a large format with all variants calls and annotated for HAE variants.
Mendoza-Alvarez A, Muñoz-Barrera A, Rubio-Rodríguez LA, Marcelino-Rodríguez I, Corrales A, Iñigo-Campos A, Callero A, Perez-Rodriguez E, García-Robaina JC, González-Montelongo R, Lorenzo-Salazar JM, Flores C. Interactive web-based resource for annotation of genetic variants causing hereditary angioedema (HADA): Database, development, implementation, and validation. Journal of Medical Internet Research 2020, 22: e19040.
HADA (Hereditary Angioedema Database Annotation) is a publicity available database which reports and annotate the variation described in Hereditary Angioedema (hereafter namely as HAE) scientific literature. Through steps of analysing and processing the genetic variation in several pathogenicity prediction tools, we develop an update database for HAE variation. This database is constructed in Shiny (R) environment for graphical interface creation for clinician easy use.
With this tool, users can upload a Variant Calling File or a list of doubt causal variation for HAE and obtain the pathogenicity prediction provided by several algorithms such as SIFT, POLYPHEN2, MUTATIONTASTER, etc, as well as obtain the pathogenicity classification established by the American College of Medical Genetics and Genomics (ACMG).
HADA is a project created by efforts of the Instituto Tecnológico y de Energías Renovables (ITER, Institute of Technology and Renewable Energies) and the Servicio Canario de la Salud (Canarian Health Service). Both entities are based in Tenerife, Canary Islands, Spain. This Shiny App runs on ITER’s Teide-HPC, which is the second most powerful computer in Spain at present.
Users can find instructions for HADA usage in the User Guide tab. If you are interested in a command-line format annotation, please see our HADA GitHub (https://github.com/genomicsITER/HADA). Changes and updates in both formats will be indicate in corresponding changelogs.
This project has been created with the efforts of several researchers from different institutions.
The total number of HADA submissions is displayed below, as well as the location of users (for statistical use only).
Number of submissions: 14