JonJala / mtag

Python command line tool for Multi-Trait Analysis of GWAS (MTAG)
GNU General Public License v3.0
171 stars 54 forks source link

GWAS to MTAG adjustment factor #214

Open gina-parcesepe opened 5 months ago

gina-parcesepe commented 5 months ago

I've followed previous advice of running the single trait MTAG to work out the factor that the MTAG beta's and SE's need to be multiplied by to compare to the GWAS results. The mean factor (MTAG_beta/GWAS_beta) is looking fine but for one of my traits the range for the factor is [0.03, 70.08]. The maxFDR for this trait is ~20% (but was ~19% in the original GWAS).

I'm not sure whether I've understood what you've said on previous issues on this matter correctly?

paturley commented 5 months ago

Hi. I'm confused by why there is a range. Isn't the single-trait MTAG roughly a constant multiple of the original GWAS summary statistics across all SNPs?

On Tue, Jun 11, 2024 at 8:40 AM gina-parcesepe @.***> wrote:

I've followed previous advice of running the single trait MTAG to work out the factor that the MTAG beta's and SE's need to be multiplied by to compare to the GWAS results. The mean factor (MTAG_beta/GWAS_beta) is looking fine but for one of my traits the range for the factor is [0.03, 70.08]. The maxFDR for this trait is ~20% (but was ~19% in the original GWAS).

I'm not sure whether I've understood what you've said on previous issues on this matter correctly?

— Reply to this email directly, view it on GitHub https://github.com/JonJala/mtag/issues/214, or unsubscribe https://github.com/notifications/unsubscribe-auth/AFBUB5POGBPHBFAJUYWR4I3ZG3V3VAVCNFSM6AAAAABJEIERGSVHI2DSMVQWIX3LMV43ASLTON2WKOZSGM2DMMZSHA2TKOI . You are receiving this because you are subscribed to this thread.Message ID: @.***>

gina-parcesepe commented 5 months ago

Hi, it is not roughly the same for one of my traits. Calculated by trait1$mtag_beta / trait2$gwas_beta , I had the following for mean [range]:

trait 1: 0.11 [0.08, 0.13] trait 2: 0.15 [0.03, 70.08] trait 3: 0.18 [0.04, 0.68]