The Seven Bridges Cancer Genomics Cloud (CGC; www.cancergenomicscloud.org) enables researchers to rapidly access and collaborate on massive public cancer genomic datasets, including The Cancer Genome Atlas. It provides secure on-demand access to data, analysis tools and computing resources. Researchers from diverse backgrounds can easily visualize, query and explore cancer genomic datasets visually or programmatically. Data of interest can be immediately analyzed in the cloud using more than 200 pre-installed, curated bioinformatics tools and workflows. Researchers can also extend the functionality of the platform by adding their own data and tools via an intuitive software development kit. By colocalizing these resources in the cloud, the CGC enables scalable, reproducible analyses. Researchers worldwide can use the CGC to investigate key questions in cancer genomics.
As RNA virus mutation occurs during replication within host cells, we hypothesized that viral evolution during acute infections in healthy hosts reflects host immune pressure. We therefore investigated the within-host diversification of human respiratory syncytial virus (RSV), a highly prevalent cause of acute respiratory infections. We evaluated healthy adults experimentally infected with an identical inoculum and infants hospitalized with naturally acquired infections. In aggregate, viral diversification in adults peaked at day 3, with overrepresentation of diversity in the matrix protein 2 (M2) and non-structural protein 2 (NS2) genes. In one subject, delayed viral clearance was accompanied by a late peak of diversity at day 10 in known and predicted B and T cell epitopes. In contrast, infant infections showed much less viral diversity. Our findings suggest multiple overlapping mechanisms for early control of acute viral infections, which may differ between age groups and host immune responses.
Increased efforts in cancer genomics research and bioinformatics are producing
tremendous amounts of data. These data are diverse in origin, format, and
content. As the amount of available sequencing data increase, technologies that
make them discoverable and usable are critically needed. In response, we have
developed a Semantic Web–based Data Browser, a tool allowing users to visually
build and execute ontology-driven queries. This approach simplifies access to
available data and improves the process of using them in analyses on the Seven
Bridges Cancer Genomics Cloud (CGC; www.cancergenomicscloud.org). The Data Browser makes large data
sets easily explorable and simplifies the retrieval of specific data of
interest. Although initially implemented on top of The Cancer Genome Atlas
(TCGA) data set, the Data Browser’s architecture allows for seamless integration
of other data sets. By deploying it on the CGC, we have enabled remote
researchers to access data and perform collaborative investigations.
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