otest_g: Jointly tests for segregation distortion and number of...
In segtest: Tests for Segregation Distortion in Polyploids

otest_g

R Documentation

Jointly tests for segregation distortion and number of incompatible genotypes

Description

This is experimental. I haven't tested it out in lots of scenarios yet.

Usage

otest_g(
  x,
  g1,
  g2,
  pbad = 0.03,
  drbound = 1/6,
  pp = TRUE,
  dr = TRUE,
  alpha = 0,
  xi1 = 1/3,
  xi2 = 1/3
)

Arguments

`x`	A vector of genotype counts. `x[i]` is the number of offspring with genotype `i-1`.
`g1`	The genotype of parent 1.
`g2`	The genotype of parent 2.
`pbad`	The upper bound on the number of bad genotypes
`drbound`	The maximum rate of double reduction. A default of 1/6 is provided, which is the rate under the complete equational segregation model of meiosis.
`pp`	A logical. Should we account for preferential pairing (`TRUE`) or not (`FALSE`)?
`dr`	A logical. Should we account for double reduction (`TRUE`) or not (`FALSE`)?
`alpha`	If `dr = FALSE`, this is the known rate of double reduction.
`xi1`	If `pp = FALSE`, this is the known preferential pairing parameter of parent 1.
`xi2`	If `pp = FALSE`, this is the known preferential pairing parameter of parent 2.

Details

Here, we test if the compatible genotypes are consistent with F1 populations and separately test that the number of incompatible genotypes isn't too large (less than 3 percent by default). This is the strategy the polymapR software uses. But we use a Bonferroni correction to combine these tests (minimum of two times the p-values), while they just multiply the p-values together. So our approach accounts for double reduction and preferential pairing, while also controlling the family-wise error rate.

Value

A list with the following elements

statistic: The log-likelihood ratio test statistic.
df: The degrees of freedom.
p_value: The Bonferroni corrected p-value.
p_lrt: The p-value of the LRT.
p_binom: The p-value of the one-sided binomial test.
alpha: The estimated double reduction rate.
xi1: The estimated preferential pairing parameter of parent 1.
xi2: The estimated preferential pairing parameter of parent 2.

Author(s)

David Gerard

Examples

# Run a test where genotypes 0, 1, and 2 are possible
x <- c(10, 10, 4, 0, 5)
otest_g(x = x, g1 = 1, g2 = 0)

# polymapR's multiplication and the Bonferroni differ
df <- expand.grid(p1 = seq(0, 1, length.out = 20), p2 = seq(0, 1, length.out = 20))
df$polymapr <- NA
df$bonferroni <- NA
for (i in seq_len(nrow(df))) {
  df$polymapr[[i]] <- df$p1[[i]] * df$p2[[i]]
  df$bonferroni[[i]] <- 2 * min(c(df$p1[[i]], df$p2[[i]], 0.5))
}
graphics::plot(df$polymapr, df$bonferroni)

segtest documentation built on July 1, 2025, 1:07 a.m.