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Implement bayesian frequency awareness #56

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cmungall opened this Issue Feb 28, 2017 · 3 comments

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cmungall commented Feb 28, 2017

Use k least frequent annotations in a probabilistic calculation, where we sum probabilities for each interpretation of the k classes (ie search space of 2^k)

cc @drseb

@cmungall cmungall self-assigned this Feb 28, 2017

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cmungall commented Mar 2, 2017

TODO

  • decide on vocabulary to use for annotating frequency associations in OWL
  • test implementation with real data
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drseb commented Mar 2, 2017 edited

Frequency: http://compbio.charite.de/hpoweb/showterm?id=HP:0040279

This is aligned with Orphanet

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jmcmurry commented May 5, 2017

From R24 "We will develop algorithms that will weight feature frequencies and negative annotations using our Bayesian ontology-querying framework89, which we will extend from a purely HPO-based algorithm to a cross-species inference algorithm accounting for species differences. Our probabilistic framework also provides a natural framework for integrating quantitative data; existing phenotype ontologies provide ready-made ‘bins’ for quantitative phenotypes, such as ‘increased body weight’ or ‘abnormal femur size’. Terms such as these are used both in the model organism literature, and by the curators of model organism databases. Sometimes this is a judgment call on the part of a researcher, but in the case of many phenotyping pipelines, normal and abnormal ranges of measurements are defined as part of the protocol. We will use these protocols and the data gather from phenotyping pipelines to learn and interpolate normal ranges for a variety of phenotypes. This will allow us to combine both qualitatively assigned abnormal ranges with quantitative data. We will also improve our capacity for differential diagnostics as well as for novel disease gene discovery by including these new advanced scoring metrics within our website as well as in our tools such as Exomiser."

@jmcmurry jmcmurry added the R24 label May 5, 2017

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