spdist: Compute genetic distances for experimental crosses

In behuang/spclust: Selective phenotyping for experimental crosses

Description

This function computes the expected percentage of markers shared IBD across the genome for experimental crosses of type backcross, doubled haploid, recombinant inbred line ("bc"), F2 ("f2"), Multiparent Advanced Generation Inter-Cross with 4 or 8 parents ("magic"), or Nested Association Mapping ("nam").

Usage

  spdist(object, type = c("bc", "f2", "magic", "nam"))

Arguments

object	cross or mpcross object containing genetic data
type	type of experimental cross

Value

distance object for use in spclust

See Also

spclust

Examples

# Simulate a map and data using qtl package
map <- sim.map(len=100, n.mar=101, eq.spacing=TRUE, include.x=FALSE)
dat1 <- sim.cross(map, n.ind=200, type="bc")
dat2 <- sim.cross(map, n.ind=500, type="f2")
# Calculate the distances between lines in datasets
dist1 <- spdist(dat1, "bc")
dist2 <- spdist(dat2, "f2")
# Heatmap of distances
heatmap(as.matrix(dist1), Rowv=NA, Colv=NA, scale="none", col=topo.colors(10))
par(mfrow=c(2, 1))
# Histogram of minimum distances between lines for full datasets
d2 <- as.matrix(dist2)
diag(d2) <- NA
mind <- apply(d2, 1, function(x) min(x, na.rm=TRUE))
hist(mind, col="tomato", main="Minimum distances between all F2 lines", xlab="Distance")
# Histogram of minimum distances between selected lines
sp <- spclust(dat2, 100, method="ward")
hist(sp$mind[, 2], col="tomato", main="Minimum distances between 100 selected F2 lines", xlab="Distance")

behuang/spclust documentation built on May 12, 2019, 10:54 a.m.