Publishing and sharing multi-dimensional image data with OMERO

Imaging data are used in the life and biomedical sciences to measure the molecular and structural composition and dynamics of cells, tissues, and organisms. Datasets range in size from megabytes to terabytes and usually contain a combination of binary pixel data and metadata that describe the acquisition process and any derived results. The OMERO image data management platform allows users to securely share image datasets according to specific permissions levels: data can be held privately, shared with a set of colleagues, or made available via a public URL. Users control access by assigning data to specific Groups with defined membership and access rights. OMERO’s Permission system supports simple data sharing in a lab, collaborative data analysis, and even teaching environments. OMERO software is open source and released by the OME Consortium at www.openmicroscopy.org

Standardisation of rates using logistic regression: a comparison with the direct method

<p>Abstract</p> <p>Background</p> <p>Standardisation of rates in health services research is generally undertaken using the direct and indirect arithmetic methods. These methods can produce unreliable estimates when the calculations are based on small numbers. Regression based methods are available but are rarely applied in practice. This study demonstrates the advantages of using logistic regression to obtain smoothed standardised estimates of the prevalence of rare disease in the presence of covariates.</p> <p>Methods</p> <p>Step by step worked examples of the logistic and direct methods are presented utilising data from BETS, an observational study designed to estimate the prevalence of subclinical thyroid disease in the elderly. Rates calculated by the direct method were standardised by sex and age categories, whereas rates by the logistic method were standardised by sex and age as a continuous variable.</p> <p>Results</p> <p>The two methods produce estimates of similar magnitude when standardising by age and sex. The standard errors produced by the logistic method were lower than the conventional direct method.</p> <p>Conclusion</p> <p>Regression based standardisation is a practical alternative to the direct method. It produces more reliable estimates than the direct or indirect method when the calculations are based on small numbers. It has greater flexibility in factor selection and allows standardisation by both continuous and categorical variables. It therefore allows standardisation to be performed in situations where the direct method would give unreliable results.</p

Broad Clade 2 Cross-Reactive Immunity Induced by an Adjuvanted Clade 1 rH5N1 Pandemic Influenza Vaccine

The availability of H5N1 vaccines that can elicit a broad cross-protective immunity against different currently circulating clade 2 H5N1 viruses is a pre-requisite for the development of a successful pre-pandemic vaccination strategy. In this regard, it has recently been shown that adjuvantation of a recombinant clade 1 H5N1 inactivated split-virion vaccine with an oil-in-water emulsion-based adjuvant system also promoted cross-immunity against a recent clade 2 H5N1 isolate (A/Indonesia/5/2005, subclade 2.1). Here we further analyse the cross-protective potential of the vaccine against two other recent clade 2 isolates (A/turkey/Turkey/1/2005 and A/Anhui/1/2005 which are, as defined by WHO, representatives of subclades 2.2 and 2.3 respectively).Two doses of the recombinant A/Vietnam/1194/2004 (H5N1, clade 1) vaccine were administered 21 days apart to volunteers aged 18-60 years. We studied the cross-clade immunogenicity of the lowest antigen dose (3.8 microg haemagglutinin) given with (N = 20) or without adjuvant (N = 20). Immune responses were assessed at 21 days following the first and second vaccine doses and at 6 months following first vaccination. Vaccination with two doses of 3.8 microg of the adjuvanted vaccine induced four-fold neutralising seroconversion rates in 85% of subjects against A/turkey/Turkey/1/2005 (subclade 2.2) and 75% of subjects against A/Anhui/1/2005 (subclade 2.3) recombinant strains. There was no response induced against these strains in the non-adjuvanted group. At 6 months following vaccination, 70% and 60% of subjects retained neutralising antibodies against the recombinant subclade 2.2 and 2.3 strains, respectively and 40% of subjects retained antibodies against the recombinant subclade 2.1 A/Indonesia/5/2005 strain.In addition to antigen dose-sparing, adjuvantation of inactivated split H5N1 vaccine promotes broad and persistent cross-clade immunity which is a pre-requisite for a pre-pandemic vaccine.ClinicalTrials.gov NCT00309634

Metadata management for high content screening in OMERO

High content screening (HCS) experiments create a classic data management challenge—multiple, large sets of heterogeneous structured and unstructured data, that must be integrated and linked to produce a set of “final” results. These different data include images, reagents, protocols, analytic output, and phenotypes, all of which must be stored, linked and made accessible for users, scientists, collaborators and where appropriate the wider community. The OME Consortium has built several open source tools for managing, linking and sharing these different types of data. The OME Data Model is a metadata specification that supports the image data and metadata recorded in HCS experiments. Bio-Formats is a Java library that reads recorded image data and metadata and includes support for several HCS screening systems. OMERO is an enterprise data management application that integrates image data, experimental and analytic metadata and makes them accessible for visualization, mining, sharing and downstream analysis. We discuss how Bio-Formats and OMERO handle these different data types, and how they can be used to integrate, link and share HCS experiments in facilities and public data repositories. OME specifications and software are open source and are available at https://www.openmicroscopy.org

Search for CP Violation in the Decay Z -> b (b bar) g

About three million hadronic decays of the Z collected by ALEPH in the years 1991-1994 are used to search for anomalous CP violation beyond the Standard Model in the decay Z -> b \bar{b} g. The study is performed by analyzing angular correlations between the two quarks and the gluon in three-jet events and by measuring the differential two-jet rate. No signal of CP violation is found. For the combinations of anomalous CP violating couplings, ${\hat{h}}_b = {\hat{h}}_{Ab}g_{Vb}-{\hat{h}}_{Vb}g_{Ab}$ and $h^{\ast}_b = \sqrt{\hat{h}_{Vb}^{2}+\hat{h}_{Ab}^{2}}$, limits of \hat{h}_b < 0.59$and$h^{\ast}_{b} < 3.02$ are given at 95\% CL.Comment: 8 pages, 1 postscript figure, uses here.sty, epsfig.st

LSST Science Book, Version 2.0

A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade. The Large Synoptic Survey Telescope (LSST) will have an effective aperture of 6.7 meters and an imaging camera with field of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over 20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a total point-source depth of r~27.5. The LSST Science Book describes the basic parameters of the LSST hardware, software, and observing plans. The book discusses educational and outreach opportunities, then goes on to describe a broad range of science that LSST will revolutionize: mapping the inner and outer Solar System, stellar populations in the Milky Way and nearby galaxies, the structure of the Milky Way disk and halo and other objects in the Local Volume, transient and variable objects both at low and high redshift, and the properties of normal and active galaxies at low and high redshift. It then turns to far-field cosmological topics, exploring properties of supernovae to z~1, strong and weak lensing, the large-scale distribution of galaxies and baryon oscillations, and how these different probes may be combined to constrain cosmological models and the physics of dark energy.Comment: 596 pages. Also available at full resolution at http://www.lsst.org/lsst/sciboo

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

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