R: Integrate TWAS and Colocalization Analysis for Gene Set Enrichment Analysis

# Integrate TWAS and Colocalization Analysis for Gene Set Enrichment Analysis

## Documentation for package ‘INTACT’ version 1.12.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

.bf_em_coloc_pi0 | Multi-INTACT EM algorithm fixed-point function.
.bf_loglik_coloc | Multi-INTACT EM algorithm log-likelihood function.
.bf_weighted_sum_coloc | Helper function for EM algorithm to compute weighted sum of Bayes factors.
.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.
.multi_em_posteriors | Compute gene product relevance probabilities using prior parameter estimates and Bayes factors.
.multi_prior_estimation | Compute Multi-INTACT prior parameter estimates and gene product relevance probabilities.
.pi1_fun | Estimate pi1 from TWAS scan z-scores.
.wakefield_bf_z_ln | A function to compute log Bayes factors from z-statistics using the Wakefield formula
chisq_sumstat | Compute a gene-level multivariate Wald chi-square statistic using summary-level genetic association and LD data.
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.
exprwt_sumstats | TWAS weights for a simulated gene.
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.
ld_sumstats | LD correlation matrix from a simulated data set.
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.
multi_intact | Compute Multi-INTACT prior parameter estimates and gene product relevance probabilities.
multi_simdat | Simulated TWAS, PWAS, and pairwise colocalization summary data.
protwt_sumstats | PWAS weights for a simulated gene.
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.
z_sumstats | TWAS and PWAS z-score for a simulated gene.