Phenotype-genotype association grid: a convenient method for summarizing multiple association analyses

BACKGROUND: High-throughput genotyping generates vast amounts of data for analysis; results can be difficult to summarize succinctly. A single project may involve genotyping many genes with multiple variants per gene and analyzing each variant in relation to numerous phenotypes, using several genetic models and population subgroups. Hundreds of statistical tests may be performed for a single SNP, thereby complicating interpretation of results and inhibiting identification of patterns of association. RESULTS: To facilitate visual display and summary of large numbers of association tests of genetic loci with multiple phenotypes, we developed a Phenotype-Genotype Association (PGA) grid display. A database-backed web server was used to create PGA grids from phenotypic and genotypic data (sample sizes, means and standard errors, P-value for association). HTML pages were generated using Tcl scripts on an AOLserver platform, using an Oracle database, and the ArsDigita Community System web toolkit. The grids are interactive and permit display of summary data for individual cells by a mouse click (i.e. least squares means for a given SNP and phenotype, specified genetic model and study sample). PGA grids can be used to visually summarize results of individual SNP associations, gene-environment associations, or haplotype associations. CONCLUSION: The PGA grid, which permits interactive exploration of large numbers of association test results, can serve as an easily adapted common and useful display format for large-scale genetic studies. Doing so would reduce the problem of publication bias, and would simplify the task of summarizing large-scale association studies

Can excitatory neuromodulation change distorted perception of one's appearance?

Body dysmorphic disorder (BDD) is marked by preoccupation with misperceived appearance flaws. Previous functional magnetic resonance imaging (fMRI) studies have found reduced neural activity and connectivity of visual areas specialized for global/holistic visual processing in BDD [[1], [2], [3]], suggesting that aberrant dorsal visual system functioning might contribute to distorted perception. In this proof-of-concept study we tested if intermittent theta-burst stimulation (iTBS), a form of excitatory repetitive transcranial magnetic stimulation (rTMS), would enhance dorsal visual system utilization as quantified through dynamic effective connectivity (DEC) modeling [4]. This is a single-session study with the application of iTBS and an fMRI scan immediately afterwards (within 15 min after the stimulation). We hypothesized that those undergoing active iTBS would show enhanced connectivity in dorsal visual areas responsible for global/holistic visual processing compared with sham

A Tabletop X-Ray Tomography Instrument for Nanometer-Scale Imaging: Integration of a Scanning Electron Microscope with a Transition-Edge Sensor Spectrometer

X-ray nanotomography is a powerful tool for the characterization of nanoscale materials and structures, but is difficult to implement due to competing requirements on X-ray flux and spot size. Due to this constraint, state-of-the-art nanotomography is predominantly performed at large synchrotron facilities. Compact X-ray nanotomography tools operated in standard analysis laboratories exist, but are limited by X-ray optics and destructive sample preparation techniques. We present a laboratory-scale nanotomography instrument that achieves nanoscale spatial resolution while changing the limitations of conventional tomography tools. The instrument combines the electron beam of a scanning electron microscope (SEM) with the precise, broadband X-ray detection of a superconducting transition-edge sensor (TES) microcalorimeter. The electron beam generates a highly focused X-ray spot in a metal target, while the TES spectrometer isolates target photons with high signal-to-noise. This combination of a focused X-ray spot, energy-resolved X-ray detection, and unique system geometry enable nanoscale, element-specific X-ray imaging in a compact footprint. The proof-of-concept for this approach to X-ray nanotomography is demonstrated by imaging 160 nm features in three dimensions in a Cu-SiO2 integrated circuit, and a path towards finer resolution and enhanced imaging capabilities is discussed.Comment: The following article has been submitted to Physical Review Applie

A tabletop x-ray tomography instrument for nanometer-scale imaging: demonstration of the 1,000-element transition-edge sensor subarray

We report on the 1,000-element transition-edge sensor (TES) x-ray spectrometer implementation of the TOMographic Circuit Analysis Tool (TOMCAT). TOMCAT combines a high spatial resolution scanning electron microscope (SEM) with a highly efficient and pixelated TES spectrometer to reconstruct three-dimensional maps of nanoscale integrated circuits (ICs). A 240-pixel prototype spectrometer was recently used to reconstruct ICs at the 130 nm technology node, but to increase imaging speed to more practical levels, the detector efficiency needs to be improved. For this reason, we are building a spectrometer that will eventually contain 3,000 TES microcalorimeters read out with microwave superconducting quantum interference device (SQUID) multiplexing, and we currently have commissioned a 1,000 TES subarray. This still represents a significant improvement from the 240-pixel system and allows us to begin characterizing the full spectrometer performance. Of the 992 maximimum available readout channels, we have yielded 818 devices, representing the largest number of TES x-ray microcalorimeters simultaneously read out to date. These microcalorimeters have been optimized for pulse speed rather than purely energy resolution, and we measure a FWHM energy resolution of 14 eV at the 8.0 keV Cu K$\alpha$ line.Comment: 5 pages, 4 figures, submitted to IEEE Transactions on Applied Superconductivit

The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: measurements of the growth of structure and expansion rate at z=0.57 from anisotropic clustering

We analyze the anisotropic clustering of massive galaxies from the Sloan Digital Sky Survey III Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 9 (DR9) sample, which consists of 264,283 galaxies in the redshift range 0.43 < z < 0.7 spanning 3,275 square degrees. Both peculiar velocities and errors in the assumed redshift-distance relation ("Alcock-Paczynski effect") generate correlations between clustering amplitude and orientation with respect to the line-of-sight. Together with the sharp baryon acoustic oscillation (BAO) standard ruler, our measurements of the broadband shape of the monopole and quadrupole correlation functions simultaneously constrain the comoving angular diameter distance (2190 +/- 61 Mpc) to z=0.57, the Hubble expansion rate at z=0.57 (92.4 +/- 4.5 km/s/Mpc), and the growth rate of structure at that same redshift (d sigma8/d ln a = 0.43 +/- 0.069). Our analysis provides the best current direct determination of both DA and H in galaxy clustering data using this technique. If we further assume a LCDM expansion history, our growth constraint tightens to d sigma8/d ln a = 0.415 +/- 0.034. In combination with the cosmic microwave background, our measurements of DA, H, and growth all separately require dark energy at z > 0.57, and when combined imply \Omega_{\Lambda} = 0.74 +/- 0.016, independent of the Universe's evolution at z<0.57. In our companion paper (Samushia et al. prep), we explore further cosmological implications of these observations.Comment: 19 pages, 11 figures, submitted to MNRAS, comments welcom

Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment