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Table 4 Results for GWAS data simulated from either a LMM or linear model with no causal SNPs

From: BGWAS: Bayesian variable selection in linear mixed models with nonlocal priors for genome-wide association studies

Nominal FDR

Method

\(n = 400\)

\(n = 2772\)

\(p = 225{,}000\)

\(p = 800{,}000\)

\(p = 225{,}000\)

\(p = 800{,}000\)

\(\kappa = 0\)

\(\kappa = 0.1\)

\(\kappa = 1\)

\(\kappa = 0\)

\(\kappa = 0.1\)

\(\kappa = 1\)

\(\kappa = 0\)

\(\kappa = 0.1\)

\(\kappa = 1\)

\(\kappa = 0\)

\(\kappa = 0.1\)

\(\kappa = 1\)

0.05

SMA-Approx.

–

0.02

0.02

–

0.00

0.14

–

0.00

0.04

–

0.00

0.00

SMA-Exact

0.02

0.02

0.02

0.02

0.00

0.14

0.12

0.00

0.04

0.12

0.00

0.00

NP, \(\tau = 0.348\)

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

NP, \(\tau = 0.022\)

0.02

0.02

0.02

0.04

0.04

0.08

0.02

0.00

0.00

0.02

0.00

0.00

NP, \(\tau\) estimated

0.02

0.00

0.02

0.02

0.02

0.02

0.00

0.00

0.00

0.00

0.00

0.00

0.1

SMA-Approx.

–

0.02

0.12

NA

0.02

0.20

–

0.04

0.08

–

0.06

0.00

SMA-Exact

0.06

0.02

0.12

0.04

0.02

0.20

0.24

0.04

0.08

0.18

0.06

0.00

NP, \(\tau = 0.348\)

0.00

0.00

0.00

0.00

0.00

0.02

0.00

0.00

0.00

0.00

0.00

0.00

NP, \(\tau = 0.022\)

0.04

0.02

0.02

0.08

0.18

0.24

0.04

0.00

0.00

0.08

0.00

0.00

NP, \(\tau\) estimated

0.02

0.02

0.04

0.02

0.08

0.06

0.00

0.00

0.00

0.00

0.00

0.00

  1. There is no approximate SMA when there is no kinship structure (i.e. \(\kappa = 0\)). Average Number of False Positives for each method over 50 datasets for each setting