A software to identify genetic mutations

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A software to identify genetic mutations

A research team developed a computer programme to identify mutations causing certain genetic diseases by analysing the genome sequencing data. The software can also detect the mutations leading to the appearance of tumours in patients with cancer. It is available to researchers all over the world.

Under the direction of Professor Stylianos Antonarakis, a research team from the Department of Genetic Medicine and Development of the Faculty of Medicine of the University of Geneva (UNIGE) developed VariantMaster, a computer program to identify mutations causing certain genetic di-seases after analysis of genome sequencing data. According to Federico A. Santoni, the principal designer, this software can also detect the mutations leading to the development of tumors in patients with cancer. VariantMaster is the subject of a publication in Genome Research and it is available to researchers all over the world.

For experts in clinical genetics, the identification of gene¬tic mutations causing certain monogenic disorders can be like looking for a needle in a haystack. A group of resear¬chers from the Faculty of Medicine of UNIGE developed an innovative software for rapidly detecting such deleterious mutations, thereby facilitating molecular diagnosis, and improving medical management for patients affected with genetic disorders, and their relatives.

An immediate success
VariantMaster, freely downloadable from sourceforge.net/pro¬­jects/variantmaster/ , is a tool for the analysis of genome sequencing data for the accurate and efficient identification of causative variants of genetic di¬seases. Close to 100 downloads in a month from China, Israel or the United States demonstrate the interest of the scientific and medical community for this tool which opens up exciting prospects for research and personalized/genomic medicine. VariantMaster was also picked up in the “Research Hi¬ghlight” section of the magazine Nature Review Genetics. If other software analyzing genome sequencing data already exist, it is, as Federico A. Santoni emphasizes, the novel probabilistic approach that makes VariantMaster a really innovative tool. For this probabilistic method, in addition to being very accurate and single-stepped, is able to prioritize the most likely genetic variants involved in a disease among tens of thousands of neutral mutations. The comparison of these variants is thus made easier and the likely causative mutations more efficiently identified.