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 <firstname.lastname@example.org>, Dipen P. Sangurdekar <email@example.com> and John D. Storey <firstname.lastname@example.org>|
|Date of publication||None|
|Maintainer||John D. Storey <email@example.com>|
plot: Graphical Display of Trigger Analysis
trigger-build: Format the input data and create an Trigger object
trigger-class: A class to store and analyze data for Transcriptional...
trigger-eigenR2: Estimate the proportion of genome-wide variation explained by...
trigger-export2cross: Export Trigger data to R/qtl's cross class object
trigger-link: Genomewide eQTL analysis
trigger-loclink: Estimate local-linkage probability for each gene
trigger-mlink: Multi-Locus Linkage (Epistasis) Analysis
trigger-net: Network-Trigger analysis
trigger-netPlot2ps: Write the network from a trigger probability matrix to a...
trigger-trait: Trait-trigger analysis
yeast: A yeast data set for Transcriptional Regulation Inference...