JAGUAR (version 3.0.1)

jaguar_cis: Perform cis-eQTL 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_cis(geneexp,genomat,snp.bed,gene.bed,cisDist=100000,nperm=10000,seed=100)

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

snp.bed

BED file format of SNP description. For more information, see http://genome.ucsc.edu/FAQ/FAQformat.html#format1 or the example data

gene.bed

BED file format of Gene description. For more information, see http://genome.ucsc.edu/FAQ/FAQformat.html#format1 or the example data

cisDist

cis distance is defined as the maximum absolute distance between the gene and a SNP. Default value is 100Kb

nperm

Number of permutations. Default value is 10,000. Note that if it is 0, no permutations are performed

seed

Seed value for permutations

Value

If permutations are performed, a list object with the following components is returned -If permutations are not performed -

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_gwa,jaguar_plotqtl

Examples

# Load the example data
data(jaguar_example);
Gene = jaguar_example$GENE_EXP
SNP = jaguar_example$GENO_MAT
gene_loc = jaguar_example$GENE_BED
snp_loc = jaguar_example$SNP_BED
# Run a cis analysis with no permutations
out = jaguar_cis(Gene,SNP,snp_loc,gene_loc,nperm=0);
length(out)