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    Analyze Human Sequence Variants
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    Integrate genome-wide
    polygenic risk scores into
    personalized medicine

GeneTalk Variant Analyzer

The Professional Network and Online Tool for Geneticists


your sequence variants with genotype frequencies, inheritance models, and expert curated gene panels.


sequence variants and find out what other GeneTalk users say about specific mutations.


with other GeneTalk users about sequence variants and their biological and medical implications. Join the large professional online network for geneticists worldwide!


your variants using powerful tools such as PEDIA and Face2Gene.

Genome-wide Polygenic Risk Scores

Many common disorders are characterized by a complex genetic component. The combined effects of many sequence variants contribute substantially to the risk of disease.

In a research setting, the inherited predisposition has already been analyzed in large case-control-studies for many phenotypes by means of polygenic risk modeling. Due to the low costs of genotyping, the resulting scores would be ideally suited for risk stratification on a population-wide scale. Indeed, most scientists do not ask themselves whether but when the predictive value of genome-wide polygenic risk scores (PRS) is robust enough to be used in personalized medicine. However, it is still unclear how a meaningful application of PRS in the clinic could look like.

We believe, that you - as a clinician scientist - will be able to develop the most innovative concepts, if you gain experience in PRS yourself. For that reason, we developed this platform where we compute a growing number of PRS that are available from the literature.

Prioritization of Exome Data by Image Analysis

The aim of the PEDIA study is to investigate the value of computer-assisted analysis of medical images and clinical features in the diagnostic workup of patients with rare genetic disorders. For this purpose, the phenotypic similarities of a patient to all known monogenic disorders (OMIM) are first quantified using next-generation phenotyping (NGP) approaches. The resulting similarity scores are then combined with deleteriousness scores from the molecular level to prioritize potential disease genes.

The performance of the approach is evaluated by assessing the diagnostic yield that can be accomplished by working through this list. For the current cohort the disease-causing gene is listed at the first position in 9 of 10 cases (top-1-accuracy rate of 91%). If you are interested in joining the study or using the software for your analysis, please contact us!

About GeneTalk

The GeneTalk project startet in July 2011. Peter Krawitz, human geneticist at Charite Berlin, had the vision of a platform, where experts in human genetics from all over the world can exchange their research results, discuss open questions and form cooperations for new projects. Further, the platform should be a tool to filter NGS data and help in analyzing patient's data. Tom Kamphans, computer scientist, liked the idea and started to work on the implementiation of the platform. In October 2011, the first version of GeneTalk went online. In 2012, GeneTalk was funded by a grand from the EU and the german ministry of economy and technology (EXIST). Peter and Tom founded the company GeneTalk GmbH in August 2013. In 2018, GeneTalk started a collaboration with FDNA for computing feature- and gestalt-scores for variants. In 2019, GeneTalk added a service for computing polygenic risk scores.