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Feedback form - Ray Stefancsik - Hi team, I am looking at this page https://monarchinitiat... #129
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Hi @rays22, These annotations infer from the gene to disease associations. So where a disease is associated with a phenotype, and that disease is associated with a gene; the third connection is made. Hope this helps. If you have have feedback or questions I am all ears! |
Thanks @iimpulse for the prompt response. The information you provided helps me to pinpoint some problems. One minor problem is that there is no provenance for the "Gene to Phenotype" associations on these pages. It is a minor problem compared with the next one, because the lack of provenance is an error of omission. However, the major problem is that many of the 'has phenotype' associations between specific genes and specific phenotypic features are false and misleading. I was hoping that there exists somewhere some reference to scientific studies that validate these associations. However, I have checked several of these gene-phenotype associations and they are not true.
At some degree, every gene is associated with every disease, but it is important to provide valid information on implied direct gene-phenotype associations. |
This is indeed an incorrect assumption - we should avoid implying this! Is there a place in the documentation that implies this @rays22 - if so we should fix it. Note this assumption doesn't even apply without the join - variable penetrance etc I agree completely that we should include more provenance. The g2p table on the HPO site is just the join of g2d and d2p, I don't see why we can't propagate more metadata from both across and include here https://hpo.jax.org/data/annotation-format. We've also discussed including evidence metadata from clingen and gencc in g2d, this could also be propagated across. |
I have not been able to find the documentation on this and I may have misunderstood the response to my query:
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While I completely agree, you can't directly relate a gene to phenotype without taking into account something like variable penetrance. Obtaining GWAS information from cohorts for each disease and their traits I would imagine is almost non-existent. Again, there is no definitive source for phenotype to gene. @pnrobinson Our first change here should be to add the predicate or metadata 'inferred' to these annotations to make it apparent that these have no direct linkage to evidence. Additionally, moving forward with evidence metadata from clingen and gencc would provide us with information about g2d, but not about p2g. Any suggestions on future implementation is greatly appreciated. |
@rays22 -- the HPOAs are all rare disease , the connection between gene and disease is much clearer than with common, complex / polygenic. |
I thought "Rare disease" is a statistical category in epidemiology. Rare genetic disease is related to the incidence of spontaneous mutations in human populations, but I am quite certain that the basic rules of scientific method and genetics still apply. Below I am hoping to clarify that the issue I have raised is unrelated to GWAS. "Penetrance" is also not the issue here, because my points apply to any non-zero penetrance phenotypic feature. By the way, how do you differentiate 0% penetrance of a phenotypic feature from any non-causal gene-allele relationship? They look the same to me. Evaluating evidence from previous experiments is very important when making a decision to support or discard a hypothesis, for example, the hypothesis of "a(ny) mutation in gene X cause phenotype Y". If gene X and gene Y alleles are associated with disease D, and disease D has a spectrum of phenotypic features P, Q, R, it is still possible that, for example, gene X alleles are never causally associated with all the phenotypic features (P, Q, R) of disease D. There are documented cases when there is extensive overlap between the gene-allele and phenotypic feature associations, but only a subset of phenotypic features of the disease can be associated with each associated gene (e.g. P and Q, but not R). As an example, could you kindly show evidence that Please, do not underestimate the risk of loosing trust in Monarch (and HPO) if you not clearly distinguish human gene - clinical phenotype associations based on evidence from associations that are only hypothetical. |
@rays22 In any case, I do not see an annotation for TNNT3 for Aplasia of radius here: https://hpo.jax.org/browse/disease/OMIM:618435 |
That is excellent news, @pnrobinson . Thank you. |
• FYI |
This annotation is coming from ORPHANET, which annotated on the basis of expert opinion and does not provide PMID citations. This particular annotation may be an error because it is reported as frequent by Orphanet but is not reported by OMIM or AFAICS in PubMed, however, there is a source: https://www.orpha.net/en/disease/sign/1147 |
Name
Ray Stefancsik
Email
stefancsik@gmail.com
GitHub Username
@rays22
Details
Page: /feedback
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Hi team,
I am looking at this page
https://monarchinitiative.org/HP:0006501?associations=biolink:GeneToPhenotypicFeatureAssociation
and I am wondering
where these Gene to Phenotype associations come from? What is the evidence for these gene-phenotype associations?
Thanks,
Ray
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