Optimization of statistical and bioinformatic methods for the analysis of next generation sequencing data for rare disease diagnosis

  1. Roca Otero, Iria
Dirigida por:
  1. María Luz Couce Pico Directora
  2. María Rosaura Leis Trabazo Codirectora

Universidad de defensa: Universidade de Santiago de Compostela

Fecha de defensa: 18 de febrero de 2020

Tribunal:
  1. José María Fraga Bermúdez Presidente
  2. María Jesús Sobrido Gómez Secretario/a
  3. David Posada González Vocal
Departamento:
  1. Departamento de Ciencias Forenses, Anatomía Patológica, Ginecología y Obstetricia y Pediatría

Tipo: Tesis

Resumen

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.