RT Dissertation/Thesis
T1 Optimization of statistical and bioinformatic methods for the analysis of next generation sequencing data for rare disease diagnosis
A1 Roca Otero, Iria
K1 Genetics
K1 Biostatistics
K1 Bioinformatics
AB The main focus of this thesis, presented as a compendium of research articles, is theoptimization of the analysis of Next Generation Sequencing data in order to facilitate thediagnosis of rare diseases. For this goal, we present an appropach to prioritize singlenucleotide variants and small insertions and deletions, not only in terms of their type andgenomic position, but also in terms of the mutational tolerance of the gene encompassingthem. We also evaluate the strengths and weakness of the currently published copy numbervariation (CNV) detection tools, and develop a methodology to create sinthetic samples withartificial CNVs to test them. Finally, we present a novel CNV-detection program, optimized forgene panel assays.
YR 2020
FD 2020
LK http://hdl.handle.net/10347/23194
UL http://hdl.handle.net/10347/23194
LA eng
DS Minerva
RD 24 abr 2026