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In the last few years, genetic researchers have started to assemble their own genetic analysis tools by reusing and combining available software. Because software development environments are not widely accepted in the Genetics community, geneticists become software developers, and they are force to integrate different solutions and to face programming issues without the required knowledge. A solution to this issue lives in the simplification of the tailored tool development. Geneticists demand development environments where: 1) the required data can be expressed according to their knowledge, and 2) the most common functionality can be easily integrated without programming skills. This PhD work proposes the use of the model-driven paradigm for addressing both concerns and presents an agile way for developing genetic analysis tools.