corrcoverage1.2.1 package

Correcting the Coverage of Credible Sets from Bayesian Genetic Fine Mapping

approx.bf.p

Find approx. Bayes factors (ABFs)

bf_func

Calculate ABFs from Z scores

cor2

Correlation matrix of SNPS

corrcov

Corrected coverage estimate using Z-scores and MAFs

corrcov_bhat

Corrected coverage estimate using estimated effect sizes and their sta...

corrcov_CI

Confidence interval for corrected coverage estimate using Z-scores and...

corrcov_CI_bhat

Confidence interval for corrected coverage estimate using estimated ef...

corrcov_nvar

Corrected coverage estimate using Z-scores and MAFs (fixing nvar)

corrcov_nvar_bhat

Corrected coverage estimate using estimated effect sizes and their sta...

corrected_cov

Corrected coverage estimate of the causal variant in the credible set

corrected_cs

Corrected credible set using Z-scores and MAFs

corrected_cs_bhat

Corrected credible set using estimated effect sizes and their standard...

credset

Credible set of genetic variants

credsetC

Credible set of variants from matrix of PPs

credsetmat

Obtain credible sets from a matrix of posterior probabilities

dot-zj_abf

Internal function: Simulate nrep ABFs from joint Z-score vector

dot-zj_pp

Simulate posterior probabilities of causality from joint Z-score vecto...

est_mu

Estimate the true effect at the causal variant using Z-scores and MAFs

est_mu_bhat

Estimate the true effect at the causal variant using estimated effect ...

logsum

logsum

logsum_matrix

logsum rows of a matrix

pipe

Pipe operator

ppfunc.mat

Find PPs of SNPs from matrix of Z-scores

ppfunc

Find PPs of SNPs from Z-scores

prop_cov

Proportion of credible sets containing the causal variant

pvals_pp

Find PPs for SNPs and null model from P-values and MAFs

Var.data.cc

Variance of the estimated effect size for case-control data

z_sim

Simulate marginal Z-scores from joint Z-score vector

z0_pp

Find PPs for SNPs and null model from Z-scores and MAFs

zj_pp

Simulate posterior probabilities of causality from joint Z-score vecto...

Using a computationally efficient method, the package can be used to find the corrected coverage estimate of a credible set of putative causal variants from Bayesian genetic fine-mapping. The package can also be used to obtain a corrected credible set if required; that is, the smallest set of variants required such that the corrected coverage estimate of the resultant credible set is within some user defined accuracy of the desired coverage. Maller et al. (2012) <doi:10.1038/ng.2435>, Wakefield (2009) <doi:10.1002/gepi.20359>, Fortune and Wallace (2018) <doi:10.1093/bioinformatics/bty898>.

  • Maintainer: Anna Hutchinson
  • License: MIT + file LICENSE
  • Last published: 2019-12-06