Bioconductor version: Release (2.12)
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.
Author: Lin S. Chen <lchen at health.bsd.uchicago.edu>, Dipen P. Sangurdekar <dps at genomics.princeton.edu> and John D. Storey <jstorey at princeton.edu>
Maintainer: John D. Storey <jstorey at princeton.edu>
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R") biocLite("trigger")
To cite this package in a publication, start R and enter:
citation("trigger")
net50.pdf | ||
R Script | Trigger Tutorial | |
Reference Manual |
biocViews | GeneExpression, GeneticVariability, Genetics, Microarray, SNP, Software |
Version | 1.6.0 |
In Bioconductor since | BioC 2.9 (R-2.14) |
License | GPL-3 |
Depends | R (>= 2.14.0), corpcor, qtl |
Imports | qvalue, methods, graphics, sva |
Suggests | |
System Requirements | |
URL | |
Depends On Me | |
Imports Me | |
Suggests Me |
Package Source | trigger_1.6.0.tar.gz |
Windows Binary | trigger_1.6.0.zip (32- & 64-bit) |
Mac OS X 10.6 (Snow Leopard) | trigger_1.6.0.tgz |
Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
Post questions about Bioconductor packages to our mailing lists. Read the posting guide before posting!