New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution, and comprehensiveness. Translating these methods to routine research and clinical practice requires robust benchmark sets. We developed the first benchmark set for identification of both false negative and false positive germline SVs, which complements recent efforts emphasizing increasingly comprehensive characterization of SVs. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle (GIAB) Consortium integrated 19 sequence-resolved variant calling methods, both alignment-and de novo assembly-based, from short-, linked-, and long-read sequencing, as well as optical and electronic mapping. The final benchmark set contains 12745 isolated, sequence-resolved insertion and deletion calls ≥50 base pairs (bp) discovered by at least 2 technologies or 5 callsets, genotyped as heterozygous or homozygous variants by long reads. The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.66 Gbp and 9641 SVs supported by at least one diploid assembly. Support for SVs was assessed using svviz with short-, linked-, and long-read sequence data. In general, there was strong support from multiple technologies for the benchmark SVs, with 90 % of the Tier 1 SVs having support in reads from more than one technology. The Mendelian genotype error rate was 0.3 %, and genotype concordance with manual curation was >98.7 %. We demonstrate the utility of the benchmark set by showing it reliably identifies both false negatives and false positives in high-quality SV callsets from short-, linked-, and long-read sequencing and optical mapping. GIAB is working towards a new version of the benchmark set that will use new technologies and methods such as PacBio Circular Consensus Sequencing and ultralong Oxford Nanopore sequencing to expand to more challenging genome regions and include more challenging SVs such as inversions. We are also developing a robust integration process to make calls on GRCh37 and GRCh38 for all seven GIAB samples.
Abstract-A broad range of embedded networked sensor (ENS) systems for critical environmental monitoring applications now require complex, high peak power dissipating sensor devices, as well as on-demand high performance computing and high bandwidth communication. Embedded computing demands for these new platforms include support for computationally intensive image and signal processing as well as optimization and statistical computing. To meet these new requirements while maintaining critical support for low energy operation, a new multiprocessor node hardware and software architecture, Low Power Energy Aware Processing (LEAP), has been developed. This architecture integrates fine-grained energy dissipation monitoring and sophisticated power control scheduling for all subsystems including sensor subsystems. The LEAP architecture enables complex energy-aware algorithm design by providing a simple interface to control numerous platform and sensor power modes and report detailed energy usage information. This paper also describes experimental results of a new distributed node testbed based on LEAP demonstrating that by exploiting high energy efficiency components and enabling proper on-demand scheduling, the LEAP architecture meets both sensing performance and energy dissipation objectives for a broad class of applications. This testbed including the network of distributed LEAP nodes and a system producing physical, mobile events provides a development environment for LEAP-hosted algorithms. New design principles, detailed implementation, and in-network programming and remote debugging capabilities of this platform are also described. While this is the first report of the LEAP system, it has been deployed for nearly one year with 50 users developing energy aware systems.Keywords-embedded wireless networked sensor, energy-aware multprocessor platform, sensor platform hardware and software architecture
Our findings suggest that the risk-factor profile and cardiovascular comorbidity of asymptomatic subjects is comparable to claudicants. Preventive efforts could be made to diminish the influence of especially smoking, diabetes and hypertension in asymptomatic subjects.
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