Description Usage Arguments Value See Also Examples
xMEabf
is supposed to conduct colocalisation analysis
integrating GWAS and eQTL summary data through Wakefield's Approximate
Bayes Factor (ABF).
1 2 | xMEabf(eqtl.summary, gwas.summary, prior.eqtl = 1e-04,
prior.gwas = 1e-04, prior.both = 1e-05)
|
eqtl.summary |
an input eQTL summary data for a region (eg the eQTLs for a gene), a list with mandatory components 'beta' (a vector for eQTL effect size), 'varbeta' (a vector for beta variance), 'N' (an integer specifying number of samples), 'MAF' (minor allele frequency, eg effect allele frequency), 'snp' (a vector for dbSNP identity) |
gwas.summary |
an input GWAS summary data, a list with mandatory components 'beta' (a vector for GWAS SNP effect size), 'varbeta' (a vector for beta variance), 'snp' (a vector for dbSNP identity) |
prior.eqtl |
the prior probability an eQTL associated with the eQTL trait. The default value is 1e-4 |
prior.gwas |
the prior probability an SNP associated with the GWAS trait. The default value is 1e-4 |
prior.both |
the prior probability an eQTL/SNP associated with both eQTL/GWAS traits. The default value is 1e-5 |
a list with two compenents (1) the component 'summary', a vector of 'nsnps' (number of SNPs analysed), 'PP.H0.abf' (posterior probabilities of H0 - no causal variant), 'PP.H1.abf' (posterior probabilities of H1 - causal variant for eQTL trait only), 'PP.H2.abf' (posterior probabilities of H2 - causal variant for GWAS trait only), 'PP.H3.abf' (posterior probabilities of H3 - two distinct causal variants), and 'PP.H4.abf' (posterior probabilities of H4 - one shared causal variant), and (2) the component 'results', a data frame with a column 'snp' (SNPs analysed), columns for eQTL statistics calcualted ('eqtl.V', 'eqtl.z', 'eqtl.r' and 'eqtl.lABF'), columns for GWAS statistics calculated ('gwas.V', 'gwas.z', 'gwas.r' and 'gwas.lABF'), a column 'both.sum.lABF' (the sum of 'eqtl.lABF' and 'gwas.lABF') and a column 'SNP.PP.H4' (the posterior probability of the SNP being causal for both traits).
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