Ughhh, suffering the plos system now. My collaborators won’t let me submit future papers to PLoS

with invaluable contributions from @temicrates Lisha Zhu @ssalazar_02 Sarah Sumner Hyunki Kim Saideep Gona @Festus_nyasimi Rohit Kulkarni @drjosephpowell @madduri
@boxiangliu

Consistency is key

I’m at UChicago, develop methods to understand the biology of complex trait and diseases, aspire to help real people with my research. Currently very optimistic about predicting molecular traits from DNA sequences using m/billions of parameters

Also worth noting: the US NIH offers financial support for those from ANY underrepresented group at ANY career stage to join an NIH funded lab!

Find a professor whose research you’re interested in and see if they are willing to host you! grants.nih.gov/grants/guide...

TWAS (transcriptome wide association study) is a statistical method that prioritizes genes that are more likely to cause a disease. It uses GWAS (genome wide association study) data, which is a method that identifies genomic loci associated with diseases

Preprint is up now www.biorxiv.org/content/10.1...

Preprint should be up shortly

4) LD is not necessary for the inflation to occur (our simulations were done using independent SNPs)

5) The inflation can be corrected by using the noncentral χ2 distribution with noncentrality parameter N h2δ Φ, where the factor Φ can be pre-calculated independent of the GWAS

2) Uncertainty in the prediction of the mediator does not cause inflation

3) Uncertainty in the prediction of the mediator reduces the power of the test

In summary

1) Polygenicity of the target trait induces inflation in the test statistics regardless of the genetic architecture of the mediating trait

Does this inflation affect other mediator-based *WAS?

Yes

What if we use PRS of GWAS traits to correlate with target traits? Is this going to be inflated?

Yes. You need to estimate Φ and use the noncentral χ2 distribution

Back to the effect of precision
Precision of prediction improves power, or equivalently prediction error reduces power but doesn’t increase inflation under the null

How well does your formula work under the alternative with finite N?

Pretty well

What happens under the alternative?

See figure for formula under the alternative

τ2 is the precision of the prediction

Can you estimate Φ?

Yes

See figure: most of the Φ are around 10e-5