| pubmed-article:17445197 | pubmed:abstractText | The Biostatistics Component of the 13th International Histocompatibility Workshop (IHWS) developed the PyPop (Python for Population Genomics) software framework for high-throughput analysis and quality control (QC) assessments of highly polymorphic genotype data. Since its initial release, the software has had several new analysis modules added to it. These additions, combined with improved data filtering and QC modules, facilitate analyses of data at different levels (allele, haplotype, amino acid sequence, and nucleotide sequence). Since the 13th IHWS, much of the human leukocyte antigen (HLA) data from the workshop, QCed via PyPop and other methods, have been made publicly available through the Major Histocompatibility Complex database web site at the National Center for Biotechnology Information (http://ncbi.nih.gov/mhc/). The Anthropology/Human Genetic Diversity component (AHGDC) data have been used in a variety of studies. Prugnolle et al. used this data to corroborate a model of pathogen-driven selection as a factor related to high levels of diversity at HLA loci. Using a comparative genomics approach contrasting results for HLA and non-HLA markers, Meyer et al. analyzed a subset of the 13th IHWS AHGDC data and showed that HLA loci show detectable signs of both natural selection and the demographic history of populations. | lld:pubmed |
