How to interpret coloc.susie results with two different variants but has very high PP.H4.Prob?
Closed this issue · 3 comments
XiaoweiHu-Stat commented
Hi,
I used coloc.susie on gwas and eqtl with summary statistics. The results show that there are two different variants in one row with very high PP.H4.Probability (e.g., 0.99). I wonder how to interpret such result since H4: both traits are associated and share the same single causal variant.
Thank you.
Xiaowei
chr1swallace commented
Are these variants in LD?
https://chr1swallace.github.io
…________________________________
From: Hu999 ***@***.***>
Sent: Friday, May 6, 2022 9:52:06 PM
To: chr1swallace/coloc ***@***.***>
Cc: Subscribed ***@***.***>
Subject: [chr1swallace/coloc] How to interpret coloc.susie results with two different variants but has very high PP.H4.Prob? (Issue #84)
Hi,
I used coloc.susie on gwas and eqtl with summary statistics. The results show that there are two different variants in one row with very high PP.H4.Probability (e.g., 0.99). I wonder how to interpret such result since H4: both traits are associated and share the same single causal variant.
Thank you.
Xiaowei
—
Reply to this email directly, view it on GitHub<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fchr1swallace%2Fcoloc%2Fissues%2F84&data=05%7C01%7Ccew54%40universityofcambridgecloud.onmicrosoft.com%7C27ae84d8d3704727e94808da2fa24962%7C49a50445bdfa4b79ade3547b4f3986e9%7C0%7C0%7C637874671301014181%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=C5vnBX6HSMqHgN%2F2c4pRyTLsnXQ7DYNKodcCPylQDcw%3D&reserved=0>, or unsubscribe<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-auth%2FAAQWR2BJCUJCXA25OLAHIRLVIWA7NANCNFSM5VJHDIFQ&data=05%7C01%7Ccew54%40universityofcambridgecloud.onmicrosoft.com%7C27ae84d8d3704727e94808da2fa24962%7C49a50445bdfa4b79ade3547b4f3986e9%7C0%7C0%7C637874671301014181%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=%2FgvvgyYGkJx%2BCTfUat%2BlgzPmge4yaR2h3KORqtXSqLM%3D&reserved=0>.
You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>
XiaoweiHu-Stat commented
Hi Chris,
Thanks for your reply. Yes, in most cases, the two variants I found in such scenario are in high LD (e.g., genetic correlation R is 0.9).
Xiaowei
…________________________________
From: Chris Wallace ***@***.***>
Sent: Saturday, May 7, 2022 3:22 PM
To: chr1swallace/coloc ***@***.***>
Cc: Hu, Xiaowei (xh6dx) ***@***.***>; Author ***@***.***>
Subject: Re: [chr1swallace/coloc] How to interpret coloc.susie results with two different variants but has very high PP.H4.Prob? (Issue #84)
Are these variants in LD?
https://chr1swallace.github.io
________________________________
From: Hu999 ***@***.***>
Sent: Friday, May 6, 2022 9:52:06 PM
To: chr1swallace/coloc ***@***.***>
Cc: Subscribed ***@***.***>
Subject: [chr1swallace/coloc] How to interpret coloc.susie results with two different variants but has very high PP.H4.Prob? (Issue #84)
Hi,
I used coloc.susie on gwas and eqtl with summary statistics. The results show that there are two different variants in one row with very high PP.H4.Probability (e.g., 0.99). I wonder how to interpret such result since H4: both traits are associated and share the same single causal variant.
Thank you.
Xiaowei
—
Reply to this email directly, view it on GitHub<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fchr1swallace%2Fcoloc%2Fissues%2F84&data=05%7C01%7Ccew54%40universityofcambridgecloud.onmicrosoft.com%7C27ae84d8d3704727e94808da2fa24962%7C49a50445bdfa4b79ade3547b4f3986e9%7C0%7C0%7C637874671301014181%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=C5vnBX6HSMqHgN%2F2c4pRyTLsnXQ7DYNKodcCPylQDcw%3D&reserved=0>, or unsubscribe<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-auth%2FAAQWR2BJCUJCXA25OLAHIRLVIWA7NANCNFSM5VJHDIFQ&data=05%7C01%7Ccew54%40universityofcambridgecloud.onmicrosoft.com%7C27ae84d8d3704727e94808da2fa24962%7C49a50445bdfa4b79ade3547b4f3986e9%7C0%7C0%7C637874671301014181%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=%2FgvvgyYGkJx%2BCTfUat%2BlgzPmge4yaR2h3KORqtXSqLM%3D&reserved=0>.
You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>
—
Reply to this email directly, view it on GitHub<#84 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AOMRHZ5JFXZEA7463DTBN5LVI27FRANCNFSM5VJHDIFQ>.
You are receiving this because you authored the thread.Message ID: ***@***.***>
chr1swallace commented
then the result says that the two traits share a causal variant, but we
are uncertain of what that variant is
…On Mon, 2022-05-09 at 05:30 -0700, Hu999 wrote:
Hi Chris,
Thanks for your reply. Yes, in most cases, the two variants I found
in
such scenario are in high LD (e.g., genetic correlation R is 0.9).
Xiaowei
________________________________
From: Chris Wallace ***@***.***>
Sent: Saturday, May 7, 2022 3:22 PM
To: chr1swallace/coloc ***@***.***>
Cc: Hu, Xiaowei (xh6dx) ***@***.***>; Author ***@***.***>
Subject: Re: [chr1swallace/coloc] How to interpret coloc.susie
results
with two different variants but has very high PP.H4.Prob? (Issue #84)
Are these variants in LD?
https://chr1swallace.github.io
________________________________
From: Hu999 ***@***.***>
Sent: Friday, May 6, 2022 9:52:06 PM
To: chr1swallace/coloc ***@***.***>
Cc: Subscribed ***@***.***>
Subject: [chr1swallace/coloc] How to interpret coloc.susie results
with
two different variants but has very high PP.H4.Prob? (Issue #84)
Hi,
I used coloc.susie on gwas and eqtl with summary statistics. The
results show that there are two different variants in one row with
very
high PP.H4.Probability (e.g., 0.99). I wonder how to interpret such
result since H4: both traits are associated and share the same single
causal variant.
Thank you.
Xiaowei
—
Reply to this email directly, view it on
GitHub<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%
2Fgithub.com%2Fchr1swallace%2Fcoloc%2Fissues%2F84&data=05%7C01%7Ccew5
4%
40universityofcambridgecloud.onmicrosoft.com%7C27ae84d8d3704727e94808
da
2fa24962%7C49a50445bdfa4b79ade3547b4f3986e9%7C0%7C0%7C637874671301014
18
1%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI
6I
k1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=C5vnBX6HSMqHgN%2F2c4pRyTL
sn
XQ7DYNKodcCPylQDcw%3D&reserved=0>, or
unsubscribe<https://eur03.safelinks.protection.outlook.com/?url=https%3
A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-
auth%2FAAQWR2BJCUJCXA25OLAHIRLVIWA7NANCNFSM5VJHDIFQ&data=05%7C01%7Cce
w5
4%40universityofcambridgecloud.onmicrosoft.com%7C27ae84d8d3704727e948
08
da2fa24962%7C49a50445bdfa4b79ade3547b4f3986e9%7C0%7C0%7C6378746713010
14
181%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBT
iI
6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=%2FgvvgyYGkJx%2BCTfUat%
2B
lgzPmge4yaR2h3KORqtXSqLM%3D&reserved=0>.
You are receiving this because you are subscribed to this
thread.Message ID: ***@***.***>
—
Reply to this email directly, view it on
GitHub<#84 (comment)-
1120270200>, or
unsubscribe<https://github.com/notifications/unsubscribe-
auth/AOMRHZ5JFXZEA7463DTBN5LVI27FRANCNFSM5VJHDIFQ>.
You are receiving this because you authored the thread.Message ID:
***@***.***>
—
Reply to this email directly, view it on GitHub, or unsubscribe.
You are receiving this because you commented.Message ID:
***@***.***>