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chr1swallace / coloc

Repo for the R package coloc
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Summary stats of two traits are from the same dataset #137

Closed Sheeya-Dong closed 10 months ago

Sheeya-Dong commented 11 months ago

If the summary stats of two traits are from the same dataset, can coloc be used for colocalisation tests?

mocksu commented 11 months ago

Do you mean from the same sample?

Sheeya-Dong commented 11 months ago

Yes. The gwas of two traits use the same samples. And if the two gwas have overlapping samples?------------------ Original ------------------From: mocksu @.>Date: Fri,Nov 3,2023 5:40 AMTo: chr1swallace/coloc @.>Cc: Sheeya-Dong @.>, Author @.>Subject: Re: [chr1swallace/coloc] Summary stats of two traits are from thesame dataset (Issue #137) Do you mean from the same sample?

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mocksu commented 11 months ago

Yes. The gwas of two traits use the same samples. And if the two gwas have overlapping samples?------------------ Original ------------------From: mocksu @.>Date: Fri,Nov 3,2023 5:40 AMTo: chr1swallace/coloc @.>Cc: Sheeya-Dong @.>, Author @.>Subject: Re: [chr1swallace/coloc] Summary stats of two traits are from thesame dataset (Issue #137) Do you mean from the same sample? —Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you authored the thread.Message ID: @.> [ { @.": "http://schema.org", @.": "EmailMessage", "potentialAction": { @.": "ViewAction", "target": "#137 (comment)", "url": "#137 (comment)", "name": "View Issue" }, "description": "View this Issue on GitHub", "publisher": { @.***": "Organization", "name": "GitHub", "url": "https://github.com" } } ]

My understanding is that colocalization does not strictly require independent samples. However, due to pleiotropy and other confounding factors, you need to pay attention to your study design and use other techniques such as bi-directional two sample Mendelian Randomization to further infer causality.

Sheeya-Dong commented 11 months ago

Got it! Thank you!

chr1swallace commented 11 months ago

mocksu is right, in all practical terms. Theoretically, coloc requires independent samples, because we take the product of likelihoods in each sample. However, once sample size is at least modest (a few hundred), we found this had limited practical impact on coloc inference - see supplementary of Mitchelmore et al (2020) https://academic.oup.com/nar/article/48/6/2866/5766659

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Got it! Thank you!

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Sheeya-Dong commented 10 months ago

I got it! Thanks a lot!