README.md
In martini: GWAS Incorporating Networks

martini

martini is an R package to perform GWAS experiment that considers prior biological knowledge. This knowledge is modeled as a network of SNPs, were edges represent functional relationships between them (e.g. belonging to the same gene). Then, it looks for regions of the network associated with the phenotype using SConES.

Installation

Install martini like any Bioconductor package:

install.packages("BiocManager")
BiocManager::install("martini")

Usage

Running martini is a three step process:

library(martini)

# 1. Read GWAS data with read.pedfile (or load the example :) )
data(minigwas)

# 2. Create the SNP network: GS (structural information), GM (GS + gene 
# annotation information) or GI (GM + protein-protein interaction information)
gs <- get_GS_network(minigwas)

# 3. Find connected, explanatory SNPs (cones)
cones <- search_cones(minigwas, gs)

# cones$selected informs about whether the SNP is selected as cones or not
head(cones)
#   snp chr cm pos allele.1 allele.2        c selected module
# 3 1A1   1  0  10        A        G 96.15385     TRUE      1
# 4 1A2   1  0  20        A        G 96.15385     TRUE      1
# 5 1A3   1  0  30        A        G 96.15385     TRUE      1
# 6 1A4   1  0  40        A        G 96.15385     TRUE      1
# 7 1A5   1  0  50        A        G 96.15385     TRUE      1
# 8 1A6   1  0  60        A        G 96.15385     TRUE      1

Please, refer to the vignettes for more detailed usage examples. martini results can be further examined using the blur package.