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Results from coloc.abf
Hi,
Thanks for developing the package, I am using coloc.abf and have run the following function:
coloc_abf_AL <- coloc.abf(dataset1 = list(beta=coloc_df$BETA, varbeta=coloc_df$Varbeta, N=1597, type="quant", MAF=coloc_df$maf, pvalues=coloc_df$P, snp=coloc_df$ID), dataset2 = list(beta=coloc_df$slope, varbeta=coloc_df$eQTL_Varbeta, N=605, type="quant", MAF=coloc_df$maf, pvalues=coloc_df$pval_nominal, snp=coloc_df$ID))
I get the result
> print(coloc_abf_AL$summary)
nsnps PP.H0.abf PP.H1.abf PP.H2.abf PP.H3.abf PP.H4.abf
3.830000e+03 6.043220e-07 8.186484e-07 4.134895e-01 5.601097e-01 2.639932e-02
I am not sure what the result means? Is this saying all my SNPs (3830) have posterior probability of 0%? Therefore, no co-localization of GWAS signals and eQTLs was found?
I also would like to ask how to interpret the result when PP.H4.abf is less than 0.95 but SNP.PP.H4 is larger than 0.95
PP.H4.abf is the primary result. If this is large, then colocalisation is likely.
If you believe colocalisation exists, then SNP.PP.H4 tells you which SNP(s) are most likely to be the shared causal variant responsible. Only consider this if PP.H4.abf is large.
-- https://chr1swallace.github.io
From: tss0222 @.> Sent: Sunday, April 2, 2023 10:26 AM To: chr1swallace/coloc @.> Cc: Subscribed @.***> Subject: Re: [chr1swallace/coloc] Results from coloc.abf (Issue #110)
I also would like to ask how to interpret the result when PP.H4.abf is less than 0.95 but SNP.PP.H4 is larger than 0.95
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This says there is a 0.026 probability of colocalisation. On the other hand, PP.H3.abf > 0.5, so my interpretation is that there are different causal variants for your two traits in this region.
-- https://chr1swallace.github.io
From: Duhh56 @.> Sent: Wednesday, December 14, 2022 3:38 PM To: chr1swallace/coloc @.> Cc: Subscribed @.***> Subject: [chr1swallace/coloc] Results from coloc.abf (Issue #110)
Hi,
Thanks for developing the package, I am using coloc.abf and have run the following function:
coloc_abf_AL <- coloc.abf(dataset1 = list(beta=coloc_df$BETA, varbeta=coloc_df$Varbeta, N=1597, type="quant", MAF=coloc_df$maf, pvalues=coloc_df$P, snp=coloc_df$ID), dataset2 = list(beta=coloc_df$slope, varbeta=coloc_df$eQTL_Varbeta, N=605, type="quant", MAF=coloc_df$maf, pvalues=coloc_df$pval_nominal, snp=coloc_df$ID))
I get the result
print(coloc_abf_AL$summary) nsnps PP.H0.abf PP.H1.abf PP.H2.abf PP.H3.abf PP.H4.abf 3.830000e+03 6.043220e-07 8.186484e-07 4.134895e-01 5.601097e-01 2.639932e-02
I am not sure what the result means? Is this saying all my SNPs (3830) have posterior probability of 0%? Therefore, no co-localization of GWAS signals and eQTLs was found?
— Reply to this email directly, view it on GitHubhttps://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fchr1swallace%2Fcoloc%2Fissues%2F110&data=05%7C01%7Ccew54%40universityofcambridgecloud.onmicrosoft.com%7Cf241e8c7204847e4d07008dadde93e42%7C49a50445bdfa4b79ade3547b4f3986e9%7C1%7C0%7C638066291078469155%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=cTETL%2FESQmreh4MC6mI7sOf%2BMsfZPdA7mL59BqlCfUE%3D&reserved=0, or unsubscribehttps://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-auth%2FAAQWR2GDYACPSO2YZ6OY4B3WNHSXDANCNFSM6AAAAAAS6UF4YA&data=05%7C01%7Ccew54%40universityofcambridgecloud.onmicrosoft.com%7Cf241e8c7204847e4d07008dadde93e42%7C49a50445bdfa4b79ade3547b4f3986e9%7C1%7C0%7C638066291078469155%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=gb6GH%2F%2FdruIU%2FhW%2BAc95NcMIXDBKAB%2B6HM9PoZb43zM%3D&reserved=0. You are receiving this because you are subscribed to this thread.Message ID: @.***>