Compositional methodology and statistical inference of family relationships using genetic markers

The present thesis is a compendium of three research articles produced between 2015 and 2019. The three articles are different contributions based on compositional statistical methodology and statistical inference of genetic 2/2 relatedness. In the first work of this thesis, we review the classical graphical methods used to detect relatedness and introduce the analysis of Compositional Data for relatedness research. In the second article, we propose the analysis of identity by state genotype sharing data instead of the classical identity by state allele sharing data. The third article finishes the thesis with the development of the likelihood ratio approach to infer three-quarter siblings in genetic databases. To illustrate all the results of this doctoral thesis we use genetic markers from worldwide human population projects such as the Human Genome Diversity Project and the 1000 Genomes Project, as well as from a local prospective human cohort of the Genomes of Catalonia (GCAT) ​
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