Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- Estimation of ancestry in the mexican population using informative genetic markers(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024) Valdez Alvarez, Héctor; Treviño Alvarado, Víctor Manuel; emipsanchez; Orozco Orozco, Lorena Sofía; García Ortiz, Humberto; Martínez Ledesma, Juan Emmanuel; Escuela de Ingeniería y Ciencias; Campus Monterrey; Garza Hernández, DeboraThe study of genetic ancestry has become an essential component of modern genetics, offering insights into the origins and migrations of human populations. This thesis presents the development of a genetic ancestry panel specifically tailored for the Mexican population, a group characterized by its high genetic diversity and complex admixture. The primary objective of this research is to accurately estimate the proportions of ancestry in Mexicans using informative genetic markers, thereby addressing the underrepresentation of this population in Genome-Wide Association Studies (GWAS). In the initial phase, various genetic databases were considered, and three were selected for the development of the ancestry panel: the 1000 Genomes Project (1000G), the Human Genome Diversity Project (HGDP), and the Metabolic Analysis in an Indigenous Sample (MAIS). The integration of these datasets provided a comprehensive view of genetic diversity crucial for the panel's accuracy. Principal Component Analysis (PCA) was employed to visualize the genetic structure and verify the separation of ancestral groups. The results confirmed the integrity of the selected datasets. Three methods for selecting Ancestry Informative Markers (AIMs)—Top K, Balanced K, and SumInfo K—were developed and evaluated. Although Balanced K and SumInfo K showed better performance than Top K, integrating Mexican data (MAIS) posed significant challenges, particularly due to the influence of East Asian populations. To address these issues, a revised strategy was implemented, focusing on optimizing AIM selection and improving the robustness of the panel. This involved a detailed workflow and validation process, ensuring the final panel's reliability. Despite the challenges, the new strategy demonstrated promising results, and the final panel is expected to be completed soon. The developed ancestry panel has significant implications for forensic science, personalized medicine, and anthropological research. By accurately estimating ancestry proportions in the Mexican population, this research contributes to a broader understanding of genetic diversity and supports more effective medical and forensic applications. Future work will focus on finalizing the panel and applying it to the oriGen project, which aims to analyze genetic data from a large cohort of Mexicans, further enhancing the understanding of this population's genetic landscape.