ACCURATE CONSTRUCTION OF LONG RANGE HAPLOTYPE IN UNRELATED INDIVIDUALS.

Haplotype, or the sequence of alleles along a single chromosome, has important applications in phenotype-genotype association studies, as well as in population genetics analyses. Because haplotype cannot be experimentally assayed in diploid organisms in a high-throughput fashion, numerous statistical methods have been developed to reconstruct probable haplotype from genotype data. These methods focus primarily on accurate phasing of a short genomic region with a small number of markers, and the error rate increases rapidly for longer regions. Here we introduce a new phasing algorithm, emphases, which aims to improve long-range phasing accuracy. Using datasets from multiple populations, we found that emphases reduces long-range phasing errors by up to 50% compared to the current state-of-the-art methods. In addition to inferring the most likely haplotypes, emphases produces confidence measures, allowing downstream analyses to account for the uncertainties associated with some haplotypes. We anticipate that emphases offers a powerful tool for analyzing large-scale data generated in the genome-wide association studies (GWAS).

A survey of rural hospitals' perspectives on health information technology outsourcing.

A survey of rural hospitals was conducted in the spring of 2012 to better understand their perspectives on health information technology (HIT) outsourcing and the role that hospital-to-hospital HIT partnerships (HHPs) can play as an outsourcing mechanism. The survey sought to understand how HHPs might be leveraged for HIT implementation, as well as the challenges with forming them. The results suggest that HHPs have the potential to address rural hospitals' slow rate of HIT adoption, but there are also challenges to creating these partnerships. These issues, as well as avenues for further research, are then discussed.

Ancestral components of admixed genomes in a Mexican cohort.

For most of the world, human genome structure at a population level is shaped by interplay between ancient geographic isolation and more recent demographic shifts, factors that are captured by the concepts of biogeographic ancestry and admixture, respectively. The ancestry of non-admixed individuals can often be traced to a specific population in a precise region, but current approaches for studying admixed individuals generally yield coarse information in which genome ancestry proportions are identified according to continent of origin. Here we introduce a new analytic strategy for this problem that allows fine-grained characterization of admixed individuals with respect to both geographic and genomic coordinates. Ancestry segments from different continents, identified with a probabilistic model, are used to construct and study "virtual genomes" of admixed individuals. We apply this approach to a cohort of 492 parent-offspring trios from Mexico City. The relative contributions from the three continental-level ancestral populations-Africa, Europe, and America-vary substantially between individuals, and the distribution of haplotype block length suggests an admixing time of 10-15 generations. The European and Indigenous American virtual genomes of each Mexican individual can be traced to precise regions within each continent, and they reveal a gradient of Amerindian ancestry between indigenous people of southwestern Mexico and Mayans of the Yucatan Peninsula. This contrasts sharply with the African roots of African Americans, which have been characterized by a uniform mixing of multiple West African populations. We also use the virtual European and Indigenous American genomes to search for the signatures of selection in the ancestral populations, and we identify previously known targets of selection in other populations, as well as new candidate loci. The ability to infer precise ancestral components of admixed genomes will facilitate studies of disease-related phenotypes and will allow new insight into the adaptive and demographic history of indigenous people.