split_families: Split a population of genotypes randomly into several...

In FielDHub: A Shiny App for Design of Experiments in Life Sciences

Split a population of genotypes randomly into several locations.

Description

Split a population of genotypes randomly into several locations, with the aim of having approximatelly the same number of replicates of each genotype, line or treatment per location.

Usage

split_families(l = NULL, data = NULL)

Arguments

l	Number of locations.
data	Data frame with the entry (ENTRY) and the labels of each treatment (NAME) and number of individuals per family group (FAMILY).

Value

A list with two elements.

• rowsEachlist is a table with a summary of cases.

• data_locations is a data frame with the entries for each location

Author(s)

Didier Murillo [aut], Salvador Gezan [aut], Ana Heilman [ctb], Thomas Walk [ctb], Johan Aparicio [ctb], Richard Horsley [ctb]

Examples

# Example 1: Split a population of 3000 and 200 families into 8 locations. 
# Original dataset is been simulated.
set.seed(77)
N <- 2000; families <- 100
ENTRY <- 1:N
NAME <- paste0("SB-", 1:N)
FAMILY <- vector(mode = "numeric", length = N)
x <- 1:N
for (i in x) { FAMILY[i] <- sample(1:families, size = 1, replace = TRUE) }
gen.list <- data.frame(list(ENTRY = ENTRY, NAME = NAME, FAMILY = FAMILY))
head(gen.list)
# Now we are going to use the split_families() function.
split_population <- split_families(l = 8, data = gen.list)
print(split_population)
summary(split_population)
head(split_population$data_locations,12)

FielDHub documentation built on Oct. 20, 2023, 1:07 a.m.