gvc_herit: Heritability

In myaseen208/gvcR: Genotypic Variance Components

Description

gvc_herit computes model based genetic heritability for given traits of different gentypes from replicated data using methodology explained by Burton, G. W. & Devane, E. H. (1953) and Allard, R.W. (2010).

Usage

gvc_herit(.data, .y, .x = NULL, .rep, .gen, .env)

## Default S3 method:
gvc_herit(.data, .y, .x = NULL, .rep, .gen, .env)

Arguments

.data	data.frame
.y	Response
.x	Covariate by default NULL
.rep	Repliction
.gen	gentypic Factor
.env	Environmental Factor

Value

Heritability

Author(s)

1. Sami Ullah ([e-mail])

2. Muhammad Yaseen ([e-mail])

References

1. Williams, E.R., Matheson, A.C. and Harwood, C.E. (2002).Experimental Design and Analysis for Tree Improvement. CSIRO Publishing.

Examples

set.seed(12345)
Response <- c(
               rnorm(48, mean = 15000, sd = 500)
             , rnorm(48, mean =  5000, sd = 500)
             , rnorm(48, mean =  1000, sd = 500)
             )
Rep      <- as.factor(rep(1:3, each = 48))
Variety  <- gl(n = 4, k =  4, length = 144, labels = letters[1:4])
Env      <- gl(n = 3, k = 16, length = 144, labels = letters[1:3])
df1      <- data.frame(Response, Rep, Variety, Env)

# Heritability
herit1 <-
  gvc_herit(
          .data  = df1
         , .y    = Response
         , .rep  = Rep
         , .gen  = Variety
         , .env  = Env
         )
herit1

library(eda4treeR)
data(DataExam6.2)
herit2 <-
  gvc_herit(
          .data  = DataExam6.2
         , .y    = Dbh.mean
         , .rep  = Replication
         , .gen  = Family
         , .env  = Province
         )
herit2

myaseen208/gvcR documentation built on May 29, 2019, 3:17 p.m.