MutationTaster: automatic vs score
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4.1 years ago
Farrel ▴ 220

Why would I care if the classification into disease vs polymorphism was automatic or not? Wouldn't the probability of the model being correct all that I need?

I am looking at whole exome sequence data in a sample of affected subjects with a rare disease. The sequences were compared to GRCH38.p2 107 and variant files were derived and then run through annovar. I can see that I have two variables related to MutationTaster: MutationTaster_score and MutationTaster_pred.

the score is the probability of the model being correct from 0 to 1
the prediction classifies as four possible predictions:

  1. "A" ("disease_causing_automatic")
  2. "D" ("disease_causing")
  3. "N" ("polymorphism")
  4. "P" ("polymorphism_automatic")

I read http://www.mutationtaster.org/info/documentation.html but am none the wiser.

genome sequence • 3.1k views
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4.1 years ago
Bioaln ▴ 350

Normally, this distinction occurs when there exist entries, manually annotated by a human being, and entries, which are the result of an automated workflow. If this is the case, I suggest you place your bets on the manual thing. (example: SwissProt vs. UniProt - TrEMBL)

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Thanks for orienting me. Here is a hyperlink to illustrate Swiss-Prot vs. TrEMBL.

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I found a slideshow online that states exactly the opposite. Look at slide number 10.

Based on the answer by @Bioaln and based on the reference at Swiss-Prot it appears as if Hina Qaiser's slides are not correct. Do you agree or can you disavow me of my misconception.

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There remains no problem, I interpret automatic as: well this protein is known to be in interaction etc., this is only semantics imho

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