The DTPreed is an accessible and powerful multiplatform application and web-based tool to investigate Variant of Unknown Significance (VUS). It provides support for consulting and analyzing 10 predicting algorithms, standardized clinical significance interpretation, interactive visualization, and genomic exploration of VUS.
Want to use DtreePred on your mobile device? Download our Android app and have powerful variant analysis tools right at your fingertips. The app provides the same comprehensive features as our web platform, optimized for mobile use.
Prefer web-based access? No problem! You can use DtreePred directly in your web browser without any installation. Our web app offers full functionality across different devices and operating systems.
A variant calling experiment, which covers mainly protein-coding genome regions, detects up to 20,000 genetic variants in patient’s DNA, many of them leading to mutations of diverse types: missense, nonsense, nonstop, frameshift, indel, synonymous, among others. Most of these alterations are harmless and a normal component of genetic diversity in humans.
Pathogenic alterations, meanwhile, can result in a wide range of uncommon and serious illnesses and the identification of pathogenic mutations is a real challenge in medicine, to precisely identify which mutation plays a critical role in diagnosis or treatments. Genotype-phenotype studies and identification of therapeutic targets are difficult and time-consuming procedures that need the professional integration and analysis of data from many dispersed sources.
The open-source online tool DTPreed and its multiplatform application, natively compiled for Android, iOS, allows a visual exploration and clinical evaluation of VUS. Through the integration of the 9 different predictor algorithms, the DTPreed supports semi-automated clinical VUS interpretation and allows real-time interactive exploration of massive datasets in an intuitive interface.
For any feedback or question about this application, to suggest new features or to report a bug, please send an email to daniel.gomes.702@ufrn.edu.br.