Linkage analysis of adult height with parent-of-origin effects in the Framingham Heart Study

Current linkage analysis methods for quantitative traits do not usually incorporate imprinting effects. Here, we carried out genome-wide linkage analysis for loci influencing adult height in the Framingham Heart Study subjects using variance components while allowing for imprinting effects. We used a sex-averaged map for the 22 autosomes, while chromosomes 6, 14, 18, and 19 were also analyzed using sex-specific maps. We compared results from these four analyses: 1) non-imprinted with sex-averaged maps, 2) imprinted with sex-averaged maps, 3) non-imprinted with sex-specific maps, and 4) imprinted with sex-specific maps. We found four regions on three chromosomes (14q32, 18p11-q21, 18q21-22, and 19q13) with LOD scores above 2.0, with a maximum LOD score of 3.12, allowing for imprinting and sex-specific maps, at D18S1364 on 18q21. While we obtained significant evidence of imprinting effects in both the 18p11-q21 and 19q13 regions when using sex-averaged maps, there were no significant differences between the imprinted and non-imprinted LOD scores when we used sex-specific maps. Our results illustrate the importance of allowing for gender-specific effects in linkage analyses, whether these are in the form of gender-specific recombination frequencies, or in the form of imprinting effects

Kinetics of High Pressure Argon-helium Pulsed Gas Discharge

Simulations of a pulsed direct current discharge are performed for a 7% argon in helium mixture at a pressure of 270 Torr using both zero- and one-dimensional models. Kinetics of species relevant to the operation of an optically pumped rare-gas laser are analyzed throughout the pulse duration to identify key reaction pathways. Time dependent densities, electron temperatures, current densities, and reduced electric fields in the positive column are analyzed over a single 20 μs pulse, showing temporal agreement between the two models. Through the use of a robust reaction rate package, radiation trapping is determined to play a key role in reducing Ar(1s5) metastable loss rates through the reaction sequence Ar(1s5)+e− → Ar(1s4)+e− followed by Ar(1s4) → Ar + ℏω⁠. Collisions with He are observed to be responsible for Ar(2p9) mixing, with nearly equal rates to Ar(2p10) and Ar(2p8) ⁠. Additionally, dissociative recombination of Ar2+ is determined to be the dominant electron loss mechanism for the simulated discharge conditions and cavity size

Effect of Ar(3p\u3csup\u3e5\u3c/sup\u3e4p; 2p)+M -\u3e Ar(3p\u3csup\u3e5\u3c/sup\u3e4s; 1s)+M branching ratio on optically pumped rare gas laser performance

Optically pumped rare gas laser performance is analyzed as a function of the Ar(3p54p; 2p) + M → Ar(3p54s; 1s) + M branching ratios. Due to the uncertainty in the branching ratios, a sensitivity study is performed to determine the effect on output and absorbed pump laser intensities. The analysis is performed using a radio frequency dielectric barrier discharge as the source of metastable production for a variety of Argon in Helium mixtures over pressures ranging from 200 to 500 Torr. Peak output laser intensities show a factor of 7 increase as the branching ratio is increased from 0.25 to 1.00. The collection of Ar* in Ar(1s4) is inversely proportional to the branching ratio and decreases output laser intensity by reducing the density of species directly involved with lasing

A comparison between microsatellite and single-nucleotide polymorphism markers with respect to two measures of information content

Using the Genetic Analysis Workshop 14 (GAW14) simulated dataset, we compare microsatellite and single-nucleotide polymorphism (SNP) markers in terms of two measures of information content, the traditional entropy-based information content measure, and a new "relative information" measure. Both attempt to measure the amount of information contained in the markers about the identity-by-descent (IBD) sharing among relatives. The performance of the two information measures are compared based on their variability and ability to predict change in the LOD score (ΔLOD) as map density increases for SNP markers. Although in a linked region, LOD scores are correlated with measures of information, we observe that none of the measures predict the LOD score itself very well. In an unlinked region, the LOD score is not related to either measures of information. The information content of microsatellite markers with 7.5-cM spacing is slightly higher than that of SNP markers with 3-cM spacing. At these map densities, microsatellites are found to be uniformly more informative than SNPs irrespective of their level of heterozygosity. For SNPs, we found that as the level of heterozygosity increases, the information content increases. As reported in all other previous studies, we also found that high-density SNPs have higher information content compared to low-density microsatellites. Performance of both the two information measures considered here are similar, but the relative information measure predicts ΔLOD as marker density increases better than the traditional entropy-based information measure

Stratified randomization controls better for batch effects in 450K methylation analysis: a cautionary tale

Background: Batch effects in DNA methylation microarray experiments can lead to spurious results if not properly handled during the plating of samples. Methods: Two pilot studies examining the association of DNA methylation patterns across the genome with obesity in Samoan men were investigated for chip- and row-specific batch effects. For each study, the DNA of 46 obese men and 46 lean men were assayed using Illumina's Infinium HumanMethylation450 BeadChip. In the first study (Sample One), samples from obese and lean subjects were examined on separate chips. In the second study (Sample Two), the samples were balanced on the chips by lean/obese status, age group, and census region. We used methylumi, watermelon, and limma R packages, as well as ComBat, to analyze the data. Principal component analysis and linear regression were respectively employed to identify the top principal components and to test for their association with the batches and lean/obese status. To identify differentially methylated positions (DMPs) between obese and lean males at each locus, we used a moderated t-test.Results: Chip effects were effectively removed from Sample Two but not Sample One. In addition, dramatic differences were observed between the two sets of DMP results. After removing'' batch effects with ComBat, Sample One had 94,191 probes differentially methylated at a q-value threshold of 0.05 while Sample Two had zero differentially methylated probes. The disparate results from Sample One and Sample Two likely arise due to the confounding of lean/obese status with chip and row batch effects.Conclusion: Even the best possible statistical adjustments for batch effects may not completely remove them. Proper study design is vital for guarding against spurious findings due to such effects

Metastable Ar(1s\u3csub\u3e5\u3c/sub\u3e) Density Dependence on Pressure and Argon-helium Mixture in a High Pressure Radio Frequency Dielectric Barrier Discharge

Simulations of an α-mode radio frequency dielectric barrier discharge are performed for varying mixtures of argon and helium at pressures ranging from 200 to 500 Torr using both zero and one-dimensional models. Metastable densities are analyzed as a function of argon-helium mixture and pressure to determine the optimal conditions, maximizing metastable density for use in an optically pumped rare gas laser. Argon fractions corresponding to the peak metastable densities are found to be pressure dependent, shifting from approximately 15% Ar in He at 200 Torr to 10% at 500 Torr. A decrease in metastable density is observed as pressure is increased due to a diminution in the reduced electric field and a quadratic increase in metastable loss rates through Ar*2 formation. A zero-dimensional effective direct current model of the dielectric barrier discharge is implemented, showing agreement with the trends predicted by the one-dimensional fluid model in the bulk plasma

Analysis of alcohol dependence phenotype in the COGA families using covariates to detect linkage

Linkage analysis methods that incorporate etiological heterogeneity of complex diseases are likely to demonstrate greater power than traditional linkage analysis methods. Several such methods use covariates to discriminate between linked and unlinked pedigrees with respect to a certain disease locus. Here we apply several such methods including two mixture models, ordered subset analysis, and a conditional logistic model to genome scan data on the DSM-IV alcohol dependence phenotype on the Collaborative Studies on Genetics of Alcoholism families, and compare the results to traditional nonparametric linkage analysis. In general, there was little agreement among the various covariate-based linkage statistics. Linkage signals with empirical p-values less than 0.001 were detected on chromosomes 3, 4, 7, 10, and 12, with the highest peak occurring at the GABRB1 gene using the ecb21 covariate