BayesA TWAS weights (t-distribution prior)

Use t-distribution as prior.

Usage

bayesAWeights(X, y, Z = NULL, ...)

Arguments

X

Numeric genotype / design matrix (samples x variants).

y

Numeric response (phenotype) vector of length nrow(X).

Z

Optional numeric matrix of fixed-effect covariates, or NULL.

...

Additional arguments forwarded to bayesAlphabetWeights / qgg.

Value

A numeric vector of effect-size weights, one per variant (column of X); columns dropped for zero variance receive weight 0.

Examples

data(eqtlRegionExample)
X <- eqtlRegionExample$X[, 1:30]
y <- eqtlRegionExample$yRes
bayesAWeights(X, y)
#> Type of analysis performed: st-blr-individual-level-dense-ld
#>  [1] -0.061904254 -0.060427059  0.019447912 -0.006202503 -0.008520610
#>  [6] -0.019719332 -0.009011315  0.050285708  0.026716389  0.016966279
#> [11] -0.016803456 -0.070378261 -0.028998764  0.023437032 -0.012037047
#> [16]  0.057617593 -0.010139959 -0.013130500  0.023757789 -0.005150303
#> [21] -0.013889153 -0.017957999 -0.007817841 -0.008491083 -0.025006316
#> [26] -0.016591899 -0.069276233 -0.010905375  0.036768380  0.011009975