detect_imputation_class: Determine whether dataset has full or top SNP statistics
In AbbVie-ComputationalGenomics/POEMColoc: Implement POEM colocalization method

Description Usage Arguments Value Examples

View source: R/detect_imputation_class.R

Determine whether dataset has full or top SNP statistics

1	detect_imputation_class(dataset)

dataset

POEMColoc formated dataset

"top" or "all'

# p-value input
dataset_full <- list(pos = c(1, 2, 3, 4, 5), MAF = c(0.14, 0.15, 0.25, 0.2, 0.4), N=1000, type ="quant", pvalues = c(2 * 10^-8, 4 * 10^-8, 2 * 10^-4, 0.6, 0.03), chr= "Z")
dataset_top_SNP <- list(pos = 2, N= 10000, s =0.5, type="cc", pvalues = 10^-9, chr = "Z")
detect_imputation_class(dataset_full)
detect_imputation_class(dataset_top_SNP)
# beta-varbeta input
dataset_full_beta_varbeta = dataset_full
dataset_full_beta_varbeta$pvalues = NULL
dataset_full_beta_varbeta$beta = c(0.5, 0.5, 0.4, 0.5, 0.26)
dataset_full_beta_varbeta$varbeta = c(0.008, 0.008, 0.012, 0.01, 0.015)
dataset_full_beta_varbeta$sdY = 1
dataset_top_SNP_beta <- list(pos = 2, N= 10000, s =0.5, type="cc", beta = 2, varbeta = 0.05, chr = "Z")
detect_imputation_class(dataset_full_beta_varbeta)
detect_imputation_class(dataset = dataset_top_SNP_beta)