Filtration of partition heritability results

[reshu23]

Dear Team,

I calculated partition heritability for ATAC seq peaks by using 106 GWAS sumstats.
For example: for "PASS.Schizophrenia.Trubetskoy2022 GWAS sumstats", I have 98 categories for peaks. I selected only category "L2_1" as partition heritability output for my peak list: Here is the output:
Category Prop._SNPs Prop.h2 Prop. h2_std_error
L2_1 3.388603e-05 0.0002310644 0.0009682196
Enrichment Enrichment_std_error Enrichment_p
6.818871 28.57283 0.8386025
Coefficient Coefficient_std_error Coefficient_z.score
8.627471e-07 3.927119e-06 0.2196896

Now I have 106 results for my peak list, which corresponds to 106 GWAS traits.
How can I select significant enriched GWAS traits in my peak list?

Which one is appropriate: calculate q value based on Enrichment_p value and filter based on q < 0.05 or consider Coefficient_z_score and calculate p and q value, then filter q < 0.05. Can you please suggest me? If I use approach 1, none of the GWAS traits will be significant in my list.
Thank you.

[aksarkar]

@reshu23 For the purposes of determining whether each trait is enriched in a given annotation, one should use the enrichment p-value. (This is different from Finucane et al. 2015, who tried to determine whether each annotation is enriched in a given trait.)

Your peak list does not cover a large enough proportion of genome to accurately estimate the coefficient or the enrichment z-score, so I am not surprised that no trait comes out with significant enrichment at FDR 0.05.

[reshu23]

Thank you.