Challenges of variant analysis in genetic testing

The February 2016 issue of Medical Lab Observer features a story co-authored by two QIAGEN Bioinformatics executives, Ramon Felciano and Michael Hadjisavas.

The story highlights the disparity between the increasing sophistication of genetic testing and the cumbersome process of variant analysis. It outlines a few key reasons for this growing gap, including the complexity of some variants, the traditional and painstaking process by which labs categorize variants, and the lack of consistency in reporting. The authors make the case that, to keep up with demand for genetic testing, the analysis piece of the puzzle needs to be fully automated, streamlined, and scalable. They call for a community-wide approach to overcome these challenges, such as the Allele Frequency Community. By sharing their resources, communities increase the value of the repository and not only help develop the market, but also improve patient diagnostics and care.

Check out the story: “Soaring demand for genetic testing highlights need for streamlined data interpretation“. The article does a great job of addressing many key considerations regarding genetic testing interpretation, the resulting glut of data, and the increasing gap between the two. We hope you enjoy reading!


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