Resumen de Characterization of the micro-substructure of a rural population from the pyrenees from a geodesic and technical point of view using ngs data
Whole genome sequencing (WGS) has boosted our current knowledge about the general architecture of the genetic diversity present in human populations. However, as we go deeper into the detection of population substructure, new methods for detecting population substructure are required and infrequent biases associated with the WGS technology become more important.
In this thesis we explore the limits of the detection of fine population substructure and their implications in the context of rural populations from the Pyrenees, and the technical artifacts generated by WGS data due to the different sequencing centres the samples were generated.
In the Introduction I talk about how variation is generated and how the frequency of new variants is modified across generations. I also recapitulate two of the more used technologies to search for variation: microarrays and next-generation sequencing (NGS). To finalize, I briefly describe the history of Homo sapiens since the out-of-Africa, recapitulate its demographic history across Europe and the importance of studying rural areas, with a particular emphasis on the Spanish Eastern Pyrenees.
In Material and Methods I describe the different datasets used in this work, with special attention to the SEP dataset. Also, I present a new algorithm to detect genetic barriers between groups of samples taking into account principles of geo-statistics. Furthermore, I also explain the use of old and new techniques to quantify levels of autozigosity in different datasets. To end this part, I show the methodology used to quantify the batch effect in the 1,000 Genomes Project dataset.
In Chapter 1 I present the results of the study of the Spanish Eastern Pyrenees dataset.
In Chapter 2 I present the results of our analysis of a possible batch effect regarding the 1,000 Genomes Project dataset affecting population genetics statistics.
