Colocalisation testing using regression coefficients
Colocalisation testing supplying only regression coefficients and their variance-covariants matrices
coloc.test.summary(b1, b2, V1, V2, k = 1, plot.coeff = FALSE, plots.extra = NULL, bayes = !is.null(bayes.factor), n.approx = 1001, level.ci = 0.95, bayes.factor = NULL, bma = FALSE)
b1 |
regression coefficients for trait 1 |
b2 |
regression coefficients for trait 2 |
V1 |
variance-covariance matrix for trait 1 |
V2 |
variance-covariance matrix for trait 2 |
k |
Theta has a Cauchy(0,k) prior. The default, k=1, is equivalent to a uniform (uninformative) prior. We have found varying k to have little effect on the results. |
plot.coeff |
DEPRECATED. Please |
plots.extra |
list with 2 named elements, x and y, equal length character vectors containing the names of the quantities to be plotted on the x and y axes.
|
bayes |
Logical, indicating whether to perform Bayesian
inference for the coefficient of proportionality, eta. If
|
level.ci, n.approx |
|
bayes.factor |
Calculate Bayes Factors to compare specific values of eta. |
bma |
parameter set to |
Typically this should be called from coloc.test()
or coloc.bma()
, but is left as a public function, to use at your own risk, if you have some other way to define the SNPs under test.
an object of class coloc, colocBayes or colocBMA
Chris Wallace
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