| Background. Single nucleotide polymorphism (SNP) genotyping arrays have been widely adopted in the study of innumerable human diseases, and in the study of human variation at the level of nucleotides and copy number variants. I theorized these data could be used at multiple levels of resolution, from the level of single individuals studied in detail to whole populations studied for trends in allele sharing.;Method. In order to study the resolution of SNP data in the study of these problems the methods used in this thesis consisted mainly of the creation and use of computation tools. To facilitate the study of individuals and small families the freely available web-based tool SNPduo was created to plot and tabulate identity by state (IBS) in SNP data between any two individuals. The study of large populations was facilitated by the creation of the portable, command-line tool SNPduo++. The examination of copy number variants was manually performed to ensure the highest quality breakpoint detection.;Results and conclusions. At the level of single individuals SNP arrays offer high resolution data that can be used to locate regions of homozygosity, as well as the location of copy number variants when probe intensity data is incorporated. The location and number of meiotic crossover events can be determined at high resolution with SNP data. Regions of Mendelian inconsistency can be located using nuclear trios, pinpointing uniparental inheritance events and copy number variation. At the level of a whole population trends in shared alleles within and between populations can be characterized, and individuals with heterogeneous geographic backgrounds can be located. Furthermore, the reported relationships between individuals can be examined and pedigrees reconstructed from the IBS analysis, allowing for quality control and the discovery of unreported relationships.;Overall SNPs provide a very flexible mechanism for discovery that goes far beyond the traditional use in linkage and association studies. By leveraging available SNP data through many disparate methods, the full power of the available information can be realized. |
