Data Priorities

Access to proteomic data of TCGA samples

Datasets containing the quantitative inventory of proteins in TCGA tumors are beginning to become available. Both mass spectrometry and affinity-based technologies are generating these data. The cloud should provide a means to connect these data to corresponding TCGA data.

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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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Correlate genome with claims & statistical data

In addition to clinical data, tie in claims data. Test feasibility of using CMS virtual data center in conjunction with the NCI cloud to link data. Other multipayer claims databases may also offer longitudinal claims histories.

 

Bring in statistical data, particularly from longitudinal studies (NLSY, HRES, NHANES) and those that have collected biospecimens. (develop standardized re-consent form)

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Construct background mutation rate

Construct background mutation rate (noise) based on the correlation of mutation frequency and expression levels or replication time. It has been shown that longer replication time and lower expression levels imply higher mutation rates among the genome (http://www.nature.com/nature/journal/v499/n7457/full/nature12213.html). Transcription-coupled DNA repair results in high expression levels and low mutation rate. So I ...more »

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