| .em_est | Compute gene set enrichment estimates. |
| .enrich_bootstrap_se | Compute bootstrap standard errors for alpha MLEs. |
| .enrich_res | Compute gene set enrichment estimates with standard errors. |
| .logistic_em | A fixed-point mapping for the expectation-maximization algorithm. Used as an argument for fixptfn in the squarem function. |
| .logistic_em_nopseudo | Similar to logistic_em(), but does not use pseudocounts to stablize the algorithm. |
| .logistic_loglik | A log likelihood function for the expectation-maximization algorithm. Used as an argument for objfn in the squarem function. |
| .pi1_fun | Estimate pi1 from TWAS scan z-scores. |
| expit | Transform a gene colocalization probability (GLCP) to a prior to be used in the evidence integration procedure. There are four prior function options, including expit, linear, step, and expit-linear hybrid. |
| fdr_rst | Bayesian FDR control for INTACT output |
| gene_set_list | Simulated gene set list. |
| hybrid | Transform a gene colocalization probability (GLCP) to a prior to be used in the evidence integration procedure. There are four prior function options, including expit, linear, step, and expit-linear hybrid. |
| intact | Compute the posterior probability that a gene may be causal, given a gene's TWAS scan z-score (or Bayes factor) and colocalization probability. |
| intactGSE | Perform gene set enrichment estimation and inference, given TWAS scan z-scores and colocalization probabilities. |
| linear | Transform a gene colocalization probability (GLCP) to a prior to be used in the evidence integration procedure. There are four prior function options, including expit, linear, step, and expit-linear hybrid. |
| simdat | Simulated TWAS and colocalization summary data. |
| step | Transform a gene colocalization probability (GLCP) to a prior to be used in the evidence integration procedure. There are four prior function options, including expit, linear, step, and expit-linear hybrid. |