A self-updating road map of The Cancer Genome Atlas.

MOTIVATION: Since 2011, The Cancer Genome Atlas' (TCGA) files have been accessible through HTTP from a public site, creating entirely new possibilities for cancer informatics by enhancing data discovery and retrieval. Significantly, these enhancements enable the reporting of analysis results that can be fully traced to and reproduced using their source data. However, to realize this possibility, a continually updated road map of files in the TCGA is required. Creation of such a road map represents a significant data modeling challenge, due to the size and fluidity of this resource: each of the 33 cancer types is instantiated in only partially overlapping sets of analytical platforms, while the number of data files available doubles approximately every 7 months. RESULTS: We developed an engine to index and annotate the TCGA files, relying exclusively on third-generation web technologies (Web 3.0). Specifically, this engine uses JavaScript in conjunction with the World Wide Web Consortium's (W3C) Resource Description Framework (RDF), and SPARQL, the query language for RDF, to capture metadata of files in the TCGA open-access HTTP directory. The resulting index may be queried using SPARQL, and enables file-level provenance annotations as well as discovery of arbitrary subsets of files, based on their metadata, using web standard languages. In turn, these abilities enhance the reproducibility and distribution of novel results delivered as elements of a web-based computational ecosystem. The development of the TCGA Roadmap engine was found to provide specific clues about how biomedical big data initiatives should be exposed as public resources for exploratory analysis, data mining and reproducible research. These specific design elements align with the concept of knowledge reengineering and represent a sharp departure from top-down approaches in grid initiatives such as CaBIG. They also present a much more interoperable and reproducible alternative to the still pervasive use of data portals. AVAILABILITY: A prepared dashboard, including links to source code and a SPARQL endpoint, is available at http://bit.ly/TCGARoadmap. A video tutorial is available at http://bit.ly/TCGARoadmapTutorial. CONTACT: robbinsd@uab.edu.

ImageJS: Personalized, participated, pervasive, and reproducible image bioinformatics in the web browser.

BACKGROUND: Image bioinformatics infrastructure typically relies on a combination of server-side high-performance computing and client desktop applications tailored for graphic rendering. On the server side, matrix manipulation environments are often used as the back-end where deployment of specialized analytical workflows takes place. However, neither the server-side nor the client-side desktop solution, by themselves or combined, is conducive to the emergence of open, collaborative, computational ecosystems for image analysis that are both self-sustained and user driven. MATERIALS AND METHODS: ImageJS was developed as a browser-based webApp, untethered from a server-side backend, by making use of recent advances in the modern web browser such as a very efficient compiler, high-end graphical rendering capabilities, and I/O tailored for code migration. RESULTS: Multiple versioned code hosting services were used to develop distinct ImageJS modules to illustrate its amenability to collaborative deployment without compromise of reproducibility or provenance. The illustrative examples include modules for image segmentation, feature extraction, and filtering. The deployment of image analysis by code migration is in sharp contrast with the more conventional, heavier, and less safe reliance on data transfer. Accordingly, code and data are loaded into the browser by exactly the same script tag loading mechanism, which offers a number of interesting applications that would be hard to attain with more conventional platforms, such as NIH's popular ImageJ application. CONCLUSIONS: The modern web browser was found to be advantageous for image bioinformatics in both the research and clinical environments. This conclusion reflects advantages in deployment scalability and analysis reproducibility, as well as the critical ability to deliver advanced computational statistical procedures machines where access to sensitive data is controlled, that is, without local "download and installation".

Waterborne outbreak of gastroenteritis associated with a norovirus.

The Wyoming Department of Health investigated an outbreak of acute gastroenteritis among persons who dined at a tourist saloon in central Wyoming during October 2001. Human caliciviruses (HuCVs) were suspected as the etiological agent of the outbreak based on the incubation period, duration of illness, and symptoms observed in ill patrons. A retrospective cohort study demonstrated that ill patrons were 4.5 times more likely to have exposure to drinking water and/or ice than nonill patrons. No food items were associated with illness. An environmental investigation gave evidence that the saloon's groundwater was contaminated with sewage. Water from the saloon's only well was processed for viruses. The processed water sample and stool samples collected from three ill patrons were analyzed by reverse transcription-PCR (RT-PCR) for the presence of HuCV. All positive RT-PCR results were confirmed by sequence and phylogenetic analyses of cloned RT-PCR products. A genogroup I, subtype 3, HuCV stain was found to be present in the well water sample and two stool samples. In addition, a genogroup II, subtype 6, strain was detected in one stool sample. The identification of the same HuCV strain in both the well water and stool samples strongly suggests a link between exposure to well water and the outbreak of gastroenteritis. The presence of a genogroup II, subtype 6, strain in one of the stool samples suggests that multiple HuCV strains may have been involved in this outbreak. The laboratory isolation of HuCV strains from outbreak-associated drinking water is relatively novel in the United States. This investigation outlines the procedure for virus isolation and illustrates the utility of RT-PCR for the identification of HuCV in large volumes of water and stool samples obtained during outbreaks of acute nonbacterial gastroenteritis.

A waterborne outbreak of Norwalk-like virus among snowmobilers-Wyoming, 2001.

In February 2001, episodes of acute gastroenteritis were reported to the Wyoming Department of Health from persons who had recently vacationed at a snowmobile lodge in Wyoming. A retrospective cohort study found a significant association between water consumption and illness, and testing identified Norwalk-like virus (NLV) in 8 of 13 stool samples and 1 well. Nucleotide sequences from the positive well-water specimen and 6 of the positive stool samples were identical. This multistrain NLV outbreak investigation illustrates the importance of NLV as a cause of waterborne illness and should encourage monitoring for NLVs in drinking water.