JAGUAR (version 3.0.1)

jaguar_gwa: Perform genome-wide analysis

Description

Computes p-value from our joint score test in a cis framework to map group-specific expression quantitative trait loci (eQTL) that tests for the shifts in gene expression patterns due to genotype and variability among tissues in a mixed effects model framework. A gene-level p-value is computed using a permutation-resampling scheme in order to investigate if a gene has at least one eQTL across all the groups.

Usage

jaguar_gwa(geneexp,genomat,write=FALSE)

Arguments

geneexp

A matrix of gene expression data with gene on rows and patient samples on columns. There has to be equal number of samples in each group. Samples (columns in the geneexp object) with missing gene expression values for any group/tissue MUST be included in the data

genomat

A matrix of genotype data recoded as single allele dosage number (i.e. 0, 1 or 2) with rows representing SNPs and columns representing samples

write

Boolean value indicating whether the results should be outputted into a tab-delimited text file. The default value is FALSE.

Value

References

Chaitanya R. Acharya, Kouros Owzar, Janice M. McCarthy and Andrew S. Allen; Exploiting expression patterns across multiple tissues to map expression quantitative trait loci. BMC Bioinformatics (2016) 17:257 DOI 10.1186/s12859-016-1123-5

See Also

jaguar_process,jaguar_slice,jaguar_sim,jaguar_cis,jaguar_plotqtl

Examples

# Load the example data
data(jaguar_example);

# Run a cis analysis with no permutations
Gene_Mat = as.matrix(jaguar_example$GENE_EXP[1:10,])
Geno_Mat = as.matrix(jaguar_example$GENO_MAT)
out = jaguar_gwa(Gene_Mat,Geno_Mat);
dim(out)