The main focus of this thesis, presented as a compendium of research articles, is the
optimization of the analysis of Next Generation Sequencing data in order to facilitate the
diagnosis of rare diseases. For this goal, we present an appropach to prioritize single
nucleotide variants and small insertions and deletions, not only in terms of their type and
genomic position, but also in terms of the mutational tolerance of the gene encompassing
them. We also evaluate the strengths and weakness of the currently published copy number
variation (CNV) detection tools, and develop a methodology to create sinthetic samples with
artificial CNVs to test them. Finally, we present a novel CNV-detection program, optimized for
gene panel assays