Chávez Viteri, Daniel EduardoGallo Camacho, Mickaela Elizabeth09/01/202509/01/20252024https://repositorio.puce.edu.ec/handle/123456789/45064Step filtering techniques in RADseq can have significant effects on population and genetic structure results. The correct selection and application of filters are crucial to ensure data accurately concerning the genetic variability present in a particular population. An 80% of filtering data prioritizes the quality and biological relevance of the SNPs, a 70% and 50% of filtering criteria seek a balance between the conservation of genomic diversity and the elimination of low-quality markers. On the other hand, 30% of filtering data seeks to maximize genomic diversification by retaining a greater number of SNPs, including less common but potentially biologically important variants. To identify how filtering criteria influence population structure results, I used a principal component analysis (PCA) to synthesize genetic similarities and differences between populations. I used different populations of the Auyan-tepui frog (Tepuihyla edelcae) from the Canaima National Park in Venezuela.esTepuihyla edelcaeGenética de poblaciónSecuencia de nucleótidosPolimorfismo de nucleótido simpleAnálisis de componente principalVariación genética