Package: trigger
Type: Package
Title: Transcriptional Regulatory Inference from Genetics of Gene
        ExpRession
Version: 1.33.0
Author: Lin S. Chen <lchen@health.bsd.uchicago.edu>, Dipen P. Sangurdekar <dps@genomics.princeton.edu> and John D. Storey <jstorey@princeton.edu>
Maintainer: John D. Storey <jstorey@princeton.edu>
Depends: R (>= 2.14.0), corpcor, qtl
Imports: qvalue, methods, graphics, sva
Description: This R package provides tools for the statistical analysis of integrative genomic data that involve some combination of: genotypes, high-dimensional intermediate traits (e.g., gene expression, protein abundance), and higher-order traits (phenotypes). The package includes functions to: (1) construct global linkage maps between genetic markers and gene expression; (2) analyze multiple-locus linkage (epistasis) for gene expression; (3) quantify the proportion of genome-wide variation explained by each locus and identify eQTL hotspots; (4) estimate pair-wise causal gene regulatory probabilities and construct gene regulatory networks; and (5) identify causal genes for a quantitative trait of interest. 
biocViews: GeneExpression, SNP, GeneticVariability, Microarray,
        Genetics
Lazyload: no
License: GPL-3
Packaged: 2019-11-07 02:39:03 UTC; biocbuild
NeedsCompilation: yes
git_url: https://git.bioconductor.org/packages/trigger
git_branch: master
git_last_commit: fea7039
git_last_commit_date: 2019-10-29
Date/Publication: 2019-11-06
Built: R 4.0.0; x86_64-apple-darwin15.6.0; 2019-11-07 15:24:21 UTC; unix
