GWAS equiv. (max) N is negative number

[AmmyDK]

Dear developer,

I run the command line as below, and I don't understand why the GWAS equiv N is an negative number, is there anything I could adjust to get the correct number?

Also, LDSC gave the genetic correlation between my two traits are 0.47, which is quite high, but here is very unexpected. Could you guide me a bit, or where I run anything wrong?

python ./mtag.py --sumstats MTAG_file1.txt,MTAG_file2.txt --out ./resultmeta --stream_stdout --perfect_gencov --equal_h2 --force

Writing Meta-analysis results to file ...

Summary of MTAG results:

---

Trait # SNPs used N (max) N (mean) GWAS mean chi^2 MTAG mean chi^2 GWAS equiv. (max) N 1 MTAG_file1.txt 4250064 1241207 1241207 1.028 0.947 -2368398 2 MTAG_file2.txt 4250064 53293 52360 0.950 0.947 55693 Omega hat not computed because --equal_h2 was used.

Calling ./mtag.py
--force
--stream-stdout
--n-min 0.0
--sumstats MTAG_file1.txt,MTAG_file2.txt
--out ./result

Summary of MTAG results:

---

Trait # SNPs used N (max) N (mean) GWAS mean chi^2 MTAG mean chi^2 GWAS equiv. (max) N 1 MTAG_file1.txt 4252732 1241207 1241207 1.028 1.026 1183887 2 MTAG_file2.txt 4252732 53293 52349 0.950 0.948 54613

Estimated Omega: [[ 2.411e-08 -2.098e-14] [-2.098e-14 -3.142e-11]]

(Correlation):
[[ 1. nan] [nan nan]]

Estimated Sigma: [[ 1.083e+00 -1.760e-04] [-1.760e-04 3.288e-05]]

(Correlation): [[ 1. -0.03] [-0.03 1. ]]

MTAG weight factors: (average across SNPs) [2.156 1.001]

Many thanks, best Ammy

[paturley]

Hi Ammy,

The problem is that the mean chi2 for trait 2 is less than 1 and therefore it implies that the trait has a negative heritability. This is usually a problem with the GWAS of the trait is too low powered. I generally don't recommend that people use MTAG unless each of the traits have a mean chi2 value of at least 1.1, and ideally greater than 1.4.

Best, Patrick

On Wed, Mar 29, 2023 at 5:44 AM Mengyu @.***> wrote:

Dear developer,

I run the command line as below, and I don't understand why the GWAS equiv N is an negative number, is there anything I could adjust to get the correct number?

Also, LDSC gave the genetic correlation between my two traits are 0.47, which is quite high, but here is very unexpected. Could you guide me a bit, or where I run anything wrong?

python ./mtag.py --sumstats MTAG_file1.txt,MTAG_file2.txt --out ./resultmeta --stream_stdout --perfect_gencov --equal_h2 --force

Writing Meta-analysis results to file ... Summary of MTAG results:

Trait # SNPs used N (max) N (mean) GWAS mean chi^2 MTAG mean chi^2 GWAS equiv. (max) N 1 MTAG_file1.txt 4250064 1241207 1241207 1.028 0.947 -2368398 2 MTAG_file2.txt 4250064 53293 52360 0.950 0.947 55693 Omega hat not computed because --equal_h2 was used.

Calling ./mtag.py --force --stream-stdout --n-min 0.0 --sumstats MTAG_file1.txt,MTAG_file2.txt --out ./result Summary of MTAG results:

Trait # SNPs used N (max) N (mean) GWAS mean chi^2 MTAG mean chi^2 GWAS equiv. (max) N 1 MTAG_file1.txt 4252732 1241207 1241207 1.028 1.026 1183887 2 MTAG_file2.txt 4252732 53293 52349 0.950 0.948 54613

Estimated Omega: [[ 2.411e-08 -2.098e-14] [-2.098e-14 -3.142e-11]]

(Correlation): [[ 1. nan] [nan nan]]

Estimated Sigma: [[ 1.083e+00 -1.760e-04] [-1.760e-04 3.288e-05]]

(Correlation): [[ 1. -0.03] [-0.03 1. ]]

MTAG weight factors: (average across SNPs) [2.156 1.001]

Many thanks, best Ammy

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