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Proteogenomics-Improved and –Guided Quantification Pipeline (PIGQpipe): Targeted Proteomics with Internal Proteogeno-typic Peptide Standards to Quantify Variants Identified by Proteogenomic Experiments


Generating solutions

Measuring proteins in biofluids such as urine or blood is critical for diagnosing, treating and monitoring disease in humans. Currently researchers and clinicians worldwide use mass spectrometry (MS) arrays to conduct multiple and parallel reaction monitoring (MRM/PRM) for this task. MRM/PRM approaches enable precise, accurate quantitation of proteins in samples, but still depend on reference human protein-sequence databases, which may be missing disease-specific genomic variants. To increase use of these approaches, therefore, the pace of assay development and validation has to increase, as does the pace of the actual sample analysis. As well, data analysis has to be standardized and automated to enable robust, large-scale implementation.

Right now, there is no sophisticated and intuitive software framework to help researchers design high-throughput mass spectrometry-based assays, process the data and interpret the results, making the process of using mass spectrometry difficult, laborious and time consuming.

Drs. Christoph Borchers and Yassene Mohammed of the University of Victoria are developing a new software pipeline, PIGQpipe, that will integrate the researchers’ own experiment-derived data with data from public online databases to generate a “one-stop shop” for all aspects of mass-spectrometry assay design, data analysis and interpretation. Using a single web-based interface, PIGQpipe will connect, integrate and automate assay workflow (including selecting targets and optimal experimental conditions), using data to calculate protein concentration values, statistically evaluating differences between treatment groups or disease conditions and presenting the data.

By increasing the productivity, scale, quality and scope of research in this area, PIGQpipe should enable new research discoveries, including tools for precision medicine; facilitate and expedite the adoption of mass-spectrometry technologies into the clinic; and build expertise in the scientific community.




2017 Bioinformatics and Computational Biology Competition

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