dist_nei: Estimation of Bray-Curtis distance

In dyerlab/gstudio: Tools Related to the Spatial Analysis of Genetic Marker Data

Estimation of Bray-Curtis distance

Description

This function returns a measure of genetic distance based upon the Nei's Genetic distance metric. Assumes drift/mutation equilibrium is the main force governing your observed differences.

Usage

dist_nei(x, stratum = "Population")

Arguments

x	A data frame with locus objects in it as well as a stratum object.
stratum	A factor indicating the stratum to use.

Value

The Nei Genetic distance

Note

This is the bias corrected Nei's Standard genetic distance.

Author(s)

Rodney J. Dyer [e-mail]

Examples

  AA <- locus( c("A","A") )
  AB <- locus( c("A","B") )
  BB <- locus( c("B","B") )
  AC <- locus( c("A","C") )
  AD <- locus( c("A","D") )
  BC <- locus( c("B","C") )
  BD <- locus( c("B","D") )
  CC <- locus( c("C","C") )
  CD <- locus( c("C","D") )
  DD <- locus( c("D","D") )
  loc1 <- c(AA,AB,AC,AD,BB,BC,BD,CC,CD,DD)
  loc2 <- c(AA,AA,AC,AA,CC,CC,AC,CC,AA,AC)
  df <- data.frame( Population=c(rep("Pop-A",5),rep("Pop-B",5)), TPI=loc1, PGM=loc2 )
  dist_nei( df )

dyerlab/gstudio documentation built on Feb. 2, 2024, 8:24 p.m.