Miles Fisher-Pollard’s scientific contributions

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Publications (1)

Fig. 1: Left: Version-controlled workflows for repeatable execution. The workflow engines of Genedata Profiler allow organizations to build and deploy standardized workflows throughout an organization, ensuring data quality and reproducibility. Example shows an RNA-Seq pipeline that was 'approved' by the study manager. Right: The best-in-class, fully interactive genome browser incorporated into Genedata Profiler facilitates visual inspection of raw data such as original short read alignments together with analysis to ensure result consistency.
Fig. 2: Automated quality control reporting. Configurable and dynamic quality reports in Genedata Profiler provide a rich set of quality metrics on NGS reads.  
Fig. 3: Left: Saving high-dimensional data to tranSMART. User selects a study from the data warehouse study tree together with other data groups to be uploaded. The data is uploaded, processed and written to tranSMART and the user notified when data is available. Right: Saving clinical data to tranSMART. Additional clinical annotations can be selected from a list by dragging and dropping. Omic and clinical annotations may be linked by choosing an appropriate field, e.g. subject ID.  
Fig. 4: Left: Initiating data transfer from tranSMART to Genedata Profiler. After selecting high-and low-dimensional data nodes in tranSMART, data is automatically transferred to the statistical module of Genedata Profiler. Middle: The Volcano Plot visualizer (top) displays a scatter plot of markers in which P-values are plotted against n-fold change. The most significant markers (red) are highly expressed after insulin treatment. A gene ontology Fisher's Exact Test (bottom) indicates that these genes are involved in cellular responses to zinc ions, which play a central role in glycemic control. Right: The Genedata Profiler platform was specifically tailored for the integration & interpretation of experimental data in translational R&D, providing a wide range of data analyses through a rich statistical toolbox and intuitive visualizations.  
Efficient genomic profiling of patients: the benefit of systems interoperability
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July 2016

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239 Reads

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2 Citations

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Miles Fisher-Pollard

Genedata ProfilerTM is a translational research software platform developed in collaboration with leading pharmaceutical companies to effectively process, manage, and analyze omic and phenotypic data to the highest standards of data quality and regulatory compliance. Genedata Profiler complements the knowledge management platform tranSMART by standardizing the processing and quality control of omics data, simplifying the publishing of data into the data warehouse, and adding sophisticated statistical analyses. In this case study we will demonstrate an end-to-end workflow to identify insulin response biomarkers utilizing the seamless, bidirectional interoperability of Genedata Profiler with tranSMART

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Citations (1)

... This integrated data will be very valuable also for the pharmaceutical companies (Schumacher et al. 2016;Regan and Payne 2015), which can mine this data and find patterns when comparing different patients' interactions with its drugs along every patient journey. This data can allow pharmaceutical companies to develop algorithms that explore improvements on the drug-patient interaction. ...

Reference:

Digital Health
Efficient genomic profiling of patients: the benefit of systems interoperability

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Miles Fisher-Pollard