Analysis Priorities

Analysis Priorities

Support multiple workflow tools and data access mechanisms

Galaxy and GenePattern are examples of systems that could provide access to data sets, pipelines, and publishable, shareable, and reproducible workflows. Ideally, existing familiar and popular platforms such as these would be supported. In addition to improving or enabling interactions between these tools, effort should be directed towards facilitating programmatic access to the underlying data in order to support custom ...more »

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12 votes
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Analysis Priorities

Actively support crowd-sourcing challenges

To stimulate learning as much as possible, as quickly as possible, the data cloud could have a utility where interested parties could pose "crowd-sourcing" challenges, e,g, Kaggle. Indeed, Harold Varmus, NCI & leaders in cancer & genomics could pose the leading questions they would like bright people to take a run at answering, e.g. Hilbert's 23 problems

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7 votes
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Analysis Priorities

Integrative Analysis of molecular datatypes for a given sample

A sample could be analyzed for DNA sequence variations, structural variations, CNVs, Gene or transcript isoform expression, genome-wide methylation patterns, ChIP-seq for specific transcription factors, metabolomic or proteomic analysis, and other molecular profiles. A framework that allows a researcher to readily identify all molecular data types associated with a particular sample and integrate the results of such analyses ...more »

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5 votes
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Analysis Priorities

Education and usability

Provide a series of online short videos and short courses that will help users adopt the new tools and instructors to incorporate into courses. (Maybe this is obvious, but high-quality tutorials and case studies take significant time to develop.)

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3 votes
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