Package: INTACT 1.13.0

Jeffrey Okamoto

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

This package integrates colocalization probabilities from colocalization analysis with transcriptome-wide association study (TWAS) scan summary statistics to implicate genes that may be biologically relevant to a complex trait. The probabilistic framework implemented in this package constrains the TWAS scan z-score-based likelihood using a gene-level colocalization probability. Given gene set annotations, this package can estimate gene set enrichment using posterior probabilities from the TWAS-colocalization integration step.

Authors:Jeffrey Okamoto [aut, cre], Xiaoquan Wen [aut]

INTACT_1.13.0.tar.gz
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INTACT_1.13.0.tgz(r-4.6-any)INTACT_1.13.0.tgz(r-4.5-any)
INTACT_1.13.0.tar.gz(r-4.7-any)INTACT_1.13.0.tar.gz(r-4.6-any)
INTACT_1.13.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
INTACT/json (API)

# Install 'INTACT' in R:

install.packages('INTACT', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jokamoto97/intact/issues

Datasets:

exprwt_sumstats - TWAS weights for a simulated gene.
gene_set_list - Simulated gene set list.
ld_sumstats - LD correlation matrix from a simulated data set.
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.
z_sumstats - TWAS and PWAS z-score for a simulated gene.

On BioConductor:INTACT-1.13.0(bioc 3.24)INTACT-1.12.0(bioc 3.23)

bayesian genesetenrichment

5.66 score 17 stars 27 scripts 9 exports 32 dependencies

Last updated from:05b3bdb6ec. Checks:1 WARNING, 7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	WARNING	162
linux-devel-x86_64	NOTE	211
source / vignettes	OK	242
linux-release-x86_64	NOTE	181
macos-release-arm64	NOTE	97
macos-oldrel-arm64	NOTE	89
windows-devel	NOTE	92
windows-release	NOTE	96
windows-oldrel	NOTE	85
wasm-release	OK	115

Exports:chisq_sumstat expit fdr_rst hybrid intact intactGSE linear multi_intact step

Dependencies:bdsmatrix cli cpp11 dplyr farver generics ggplot2 glue gtable isoband labeling lifecycle magrittr numDeriv pillar pkgconfig purrr R6 RColorBrewer rlang S7 scales SQUAREM stringi stringr tibble tidyr tidyselect utf8 vctrs viridisLite withr

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

Rendered fromINTACT.Rmdusingknitr::rmarkdown

Last update: 2024-10-01
Started: 2022-12-13

Help page	Topics
Multi-INTACT EM algorithm fixed-point function.	.bf_em_coloc_pi0
Multi-INTACT EM algorithm log-likelihood function.	.bf_loglik_coloc
Helper function for EM algorithm to compute weighted sum of Bayes factors.	.bf_weighted_sum_coloc
Compute gene set enrichment estimates.	.em_est
Compute bootstrap standard errors for alpha MLEs.	.enrich_bootstrap_se
Compute gene set enrichment estimates with standard errors.	.enrich_res
A fixed-point mapping for the expectation-maximization algorithm. Used as an argument for fixptfn in the squarem function.	.logistic_em
Similar to logistic_em(), but does not use pseudocounts to stablize the algorithm.	.logistic_em_nopseudo
A log likelihood function for the expectation-maximization algorithm. Used as an argument for objfn in the squarem function.	.logistic_loglik
Compute gene product relevance probabilities using prior parameter estimates and Bayes factors.	.multi_em_posteriors
Compute Multi-INTACT prior parameter estimates and gene product relevance probabilities.	.multi_prior_estimation
Estimate pi1 from TWAS scan z-scores.	.pi1_fun
A function to compute log Bayes factors from z-statistics using the Wakefield formula	.wakefield_bf_z_ln
Compute a gene-level multivariate Wald chi-square statistic using summary-level genetic association and LD data.	chisq_sumstat
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.	expit
TWAS weights for a simulated gene.	exprwt_sumstats
Bayesian FDR control for INTACT output	fdr_rst
Simulated gene set list.	gene_set_list
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.	hybrid
Compute the posterior probability that a gene may be causal, given a gene's TWAS scan z-score (or Bayes factor) and colocalization probability.	intact
Perform gene set enrichment estimation and inference, given TWAS scan z-scores and colocalization probabilities.	intactGSE
LD correlation matrix from a simulated data set.	ld_sumstats
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.	linear
Compute Multi-INTACT prior parameter estimates and gene product relevance probabilities.	multi_intact
Simulated TWAS, PWAS, and pairwise colocalization summary data.	multi_simdat
PWAS weights for a simulated gene.	protwt_sumstats
Simulated TWAS and colocalization summary data.	simdat
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.	step
TWAS and PWAS z-score for a simulated gene.	z_sumstats

Package: INTACT 1.13.0

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

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