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Design of the CART data system for the US Department of Energy's ARM Program
The Department of Energy (DOE) has initiated a major atmospheric research effort to reduce the uncertainties found in general circulation and other models due to the effects of clouds and radiation. The objective of the Atmospheric Radiation Measurement Program (ARM) is to provide an experimental testbed for the study of important atmospheric effects, particularly cloud and radiative processes, and testing parameterizations of the processes for use in atmospheric models. This experimental testbed, known as the Clouds and Radiation Testbed (CART), will include a complex data system, the CART Data Environment (CDE). The major functions of the CDE will be to: acquire environments from instruments and external data sources; perform quality assessments of the data streams; create data streams of known quality to be used as model input compared to model output; execute the models and capture their predictions; and make data streams associated with model tests available to ARM investigators in near real-time. The CDE will also be expected to capture ancillary information ( meta-data'') associated with the data streams, provide data management facilities for design of ARM experiments, and provide for archival data storage. The first section of this paper presents background information on CART. Next the process for the functional design of the system is described, the functional requirements summarized, and the conceptual architecture of the CDE is presented. Finally, the status of the CDE design activities is summarized, and major technical challenges are discussed
Cohort Profile: Pregnancy And Childhood Epigenetics (PACE) Consortium.
Development Psychopathology in context: famil
Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation
DNA methylation quantitative trait locus (mQTL) analyses on 32,851 participants identify genetic variants associated with DNA methylation at 420,509 sites in blood, resulting in a database of >270,000 independent mQTLs.Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.Molecular Epidemiolog
Incidence of Lumbar Disc Surgery : A Population-Based Study in Olmsted County, Minnesota, 1950-1979.
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