diseq {GeneticsBase}R Documentation

Estimate or Compute Confidence Interval for the Single-Marker Disequilibrium

Description

Estimate or compute confidence interval for single-marker disequilibrium.

Usage

diseq.ci(object, marker, R = 1000, conf = 0.95, correct = TRUE, na.rm =
TRUE, ...)
diseq.inner(object, marker, ...)

Arguments

object geneSet object
marker marker names
R Number of bootstrap iterations to use when computing the confidence interval. Defaults to 1000.
conf Confidence level to use when computing the confidence level for D-hat. Defaults to 0.95, should be in (0,1).
correct See details.
na.rm logical. Should missing values be removed?
... optional additional parameters passed

Details

For a single-gene marker, diseq computes the Hardy-Weinberg (dis)equilibrium statistic D, D', r (the correlation coefficient), and r^2 for each pair of allele values, as well as an overall summary value for each measure across all alleles. print.diseq displays the contents of a diseq object. diseq.ci computes a bootstrap confidence interval for this estimate.

For consistency, I have applied the standard definitions for D, D', and r from the Linkage Disequilibrium case, replacing all marker probabilities with the appropriate allele probabilities.

Thus, for each allele pair,

where

When there are more than two alleles, the summary values for these statistics are obtained by computing a weighted average of the absolute value of each allele pair, where the weight is determined by the expected frequency. For example:

D.overall = sum |D(ij)| * p(ij)

Bootstrapping is used to generate confidence interval in order to avoid reliance on parametric assumptions, which will not hold for alleles with low frequencies (e.g. D' following a a Chi-square distribution).

See the function {HWE} from "genetics" package for testing Hardy-Weinberg Equilibrium, D=0.

Author(s)

Gregory R. Warnes warnes@bst.rochester.edu and Nitin Jain nitin.jain@pfizer.com


[Package GeneticsBase version 1.8.0 Index]