Probability-based detection of phosphoproteomic uncertainty reveals rare signaling events driven by oncogenic kinase gene fusion

Robin, X.; Voellmy, F.; Ferkinghoff-Borg, J.; Howard, C.; Altenburg, T.; Engel, M.; Simpson, C.; Saginc, G.; Koplev, S.; Klipp, E.; Longden, J.; Linding, R.

doi:10.1101/621961

bioRxiv · 10.1101/621961

Probability-based detection of phosphoproteomic uncertainty reveals rare signaling events driven by oncogenic kinase gene fusion

Robin, X.·Voellmy, F.·Ferkinghoff-Borg, J.·Howard, C.·Altenburg, T.·Engel, M.·Simpson, C.·Saginc, G.·Koplev, S.·Klipp, E.·Longden, J.·Linding, R.

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Abstract

We describe a novel Bayesian method for estimating protein concentration and phosphorylation site occupancy ratios from mass spectrometry experiments. Our variance model assigns standard deviations to all quantitative ratios, even when only a single peptide is observed, increasing the number of quantifiable observations in a sample compared to conventional methods. We further demonstrate the application of this method using a dataset investigating the impact of the PRKAR1A-RET gene fusion in immortalized thyroid cells.

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Robin, X., Voellmy, F., Ferkinghoff-Borg, J., Howard, C., Altenburg, T., Engel, M., Simpson, C., Saginc, G., Koplev, S., Klipp, E., Longden, J., Linding, R.. 2019-04-29. Probability-based detection of phosphoproteomic uncertainty reveals rare signaling events driven by oncogenic kinase gene fusion. https://doi.org/10.1101/621961

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