int_neighbor: Testing marker-by-marker epistasis in neighbor QTL effects

In rNeighborQTL: Interval Mapping for Quantitative Trait Loci Underlying Neighbor Effects

Description

A function to test interaction terms between one focal marker and the other markers across a genome.

Usage

int_neighbor(
  genoprobs,
  pheno,
  smap,
  scale,
  addcovar = NULL,
  addQTL,
  intQTL,
  grouping = rep(1, nrow(smap)),
  response = c("quantitative", "binary"),
  contrasts = NULL
)

Arguments

genoprobs	Conditional genotype probabilities as taken from qtl::calc.genoprob().
pheno	A vector of individual phenotypes.
smap	A matrix showing a spatial map for individuals. The first and second column include spatial positions along an x-axis and y-axis, respectively.
scale	A numeric scalar indicating the maximum spatial distance between a focal individual and neighbors to define neighbor effects.
addcovar	An optional matrix including additional non-genetic covariates. It contains no. of individuals x no. of covariates.
addQTL	A vector containing marker names that are considered covariates. This argument is necessary for int_neighbor(), and must match the marker names of gmap.
intQTL	A name of a focal marker to be tested for its epistasis with the other markers in neighbor effects. The marker name must be included by addQTL.
grouping	An optional integer vector assigning each individual to a group. This argument can be used when smap contains different experimental replicates. Default setting means that all individuals are belong to a single group.
response	An optional argument to select trait types. The "quantitative" or "binary" calls the "gaussian" or "binomial" family in glm(), respectively.
contrasts	An optional vector composed of three TRUE/FALSE values, which represents the presence/absence of specific genotypes as c(TRUE/FALSE, TRUE/FALSE, TRUE/FALSE) = AA, AB, BB. If NULL, it is compiled from genoprobs automatically.

Details

This is an optimal function to test two-way interactions between the main neighbor effect of a focal marker given by intQTL and the others. All the main neighbor effects are first estimated using eff_neighbor(), and then a two-way interaction term between the focal marker effect and its counterpart was considered an additional explanatory variable. LOD score was compared between models with or without the two-way interaction.

Value

A matrix of LOD scores for neighbor epistasis effects, with the chromosome numbers and positions. The row names correspond to marker names.

• chr Chromosome number

• pos Marker position

• LOD_int LOD score for epistasis in neighbor effects between a focal and the other markers

Author(s)

Yasuhiro Sato ([e-mail])

See Also

scan_neighbor eff_neighbor

Examples

set.seed(1234)
test_map <- qtl::sim.map(len=rep(20,5),n.mar=3,include.x=FALSE)
test_cross <- qtl::sim.cross(test_map,n.ind=50)
test_smap <- cbind(runif(50,1,100),runif(50,1,100))
test_genoprobs <- qtl::calc.genoprob(test_cross,step=2)

test_int <- int_neighbor(genoprobs=test_genoprobs,
                         pheno=test_cross$pheno$phenotype,
                         smap=test_smap,scale=20,
                         addQTL=c("c1_D1M1","c1_D1M2"),intQTL="c1_D1M1"
                         )
plot_nei(test_int, type="int")

rNeighborQTL documentation built on April 9, 2021, 9:06 a.m.