est.coi {xoi}

Estimate the coincidence function

Description

Estimate the coincidence function from backcross data.

Usage

est.coi(
  cross,
  chr = NULL,
  pos = NULL,
  window = 0,
  fill.method = c("imp", "argmax"),
  error.prob = 0.0000000001,
  map.function = c("haldane", "kosambi", "c-f", "morgan")
)

Arguments

cross

Cross object; must be a backcross. See qtl::read.cross() for format details.

chr

Chromosome to consider (only one is allowed). If NULL, the first chromosome is considered.

pos

If provided, these are used as the marker positions. (This could be useful if you want to do things with respect to physical distance.)

window

Window size used to smooth the estimates.

fill.method

Method used to impute missing data.

error.prob

Genotyping error probability used in imputation of missing data.

map.function

Map function used in imputation of missing data.

Details

The coincidence function is the probability of a recombination event in both of two intervals, divided by the product of the two recombination fractions. We estimate this as a function of the distance between the two intervals.

Note that we first call qtl::fill.geno() to impute any missing genotype data.

Value

A data.frame containing the distance between intervals and the corresponding estimate of the coincidence. There are actually two columns of estimates of the coincidence. In the first estimate, we take a running mean of each of the numerator and denominator and then divide. In the second estimate, we first take a ratio and then take a running mean.

Author(s)

Karl W Broman, [e-mail]

References

McPeek, M. S. and Speed, T. P. (1995) Modeling interference in genetic recombination. Genetics 139, 1031–1044.

See Also

gammacoi(), stahlcoi(), kfunc()

Examples

map1 <- sim.map(103, n.mar=104, anchor=TRUE, include.x=FALSE, eq=TRUE)
x <- sim.cross(map1, n.ind=2000, m=6, type="bc")

out <- est.coi(x, window=5)
plot(coi1 ~ d, data=out, type="l", lwd=2, col="blue")
lines(coi2 ~ d, data=out, lwd=2, col="green")
lines(gammacoi(7), lwd=2, col="red", lty=2)