run_conditional_gwas: Conditional analysis for known complex trait-associated...
In kjgleason/Primo: Package in R for Integrative Multi-Omics association analysis

For specified, known complex trait-associated (GWAS) variant(s), set-up and run conditional analysis. The function identifies lead omics SNPs to consider for conditional analysis, and determines which SNPs will be conditioned on for each GWAS variant based on specified criteria. Returns a data.frame with posterior probabilities for collapsed association patterns and results from conditional analysis. Also returns a vector of estimated FDR for each collapsed association pattern at a specified posterior probability threshold.

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run_conditional_gwas(Primo_obj, IDs, gwas_snps, pvals, LD_mat, snp_info,
  pp_thresh, LD_thresh = 0.9, dist_thresh = 5000,
  pval_thresh = 0.001, gwas_col = 1, use_ID_labels = TRUE)

`Primo_obj`	list returned by running the t-statistic version of Primo (i.e. `Primo_tstat`)
`IDs`	data.frame of the SNP and phenotype IDs corresponding to each row of the Primo results stored in `Primo_obj`.
`gwas_snps`	character vector of known trait-associated (GWAS) SNPs.
`pvals`	matrix of P-values from test statistics.
`LD_mat`	matrix of genotype correlation coefficients (e.g. Pearson r). Row and column names should be SNP/variant names (i.e matching variant names in `IDs`).
`snp_info`	data.frame reporting the chromosome and position of each SNP. Columns must include: `SNP, CHR, POS`.
`pp_thresh`	scalar of the posterior probability threshold used for significance.
`LD_thresh`	scalar corresponding to the LD r^2 threshold to be used for conditional analysis. Lead omics SNPs with r^2 < `LD_thresh` with the GWAS SNP will be conditioned on.
`dist_thresh`	scalar of the minimum number of base pairs away from the GWAS SNP that a lead SNP must be in order to be conditioned on.
`pval_thresh`	scalar of the P-value threshold a lead SNP must be below with the phenotype for which it is lead SNP in order to be conditioned on.
`gwas_col`	integer of the data column (e.g. in `Primo_obj$Tstat_mod`) of the GWAS study. Default is the first data column.
`use_ID_labels`	logical of whether or not phenotype column names in `IDs` should be used as labels for identifying possible omics associations. If `FALSE`, labels will append j to 'study', where j is the corresponding data column of the omics phenotype.

A list with two elements, pp_grouped and fdr.

fdr is a named vector of the estimated false discovery rates (FDR) for each collapsed association pattern at the posterior probability threshold, pp_thresh.

pp_grouped is a data.frame with the following information:

SNP and trait identifiers corresponding to each observation
posterior probabilities of the collapsed association patterns ("GWAS + at least n omics trait(s)")
number of omics traits with which the SNP was associated before conditional analysis (at posterior probability > pp_thresh)
number of omics traits with which the SNP is associated after conditional analysis
top association pattern before conditional analysis
top association pattern after conditional analysis
omics traits with which SNP may be associated based on top patterns before and after conditional analysis