split_families {FielDHub} | R Documentation |
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)
[Package FielDHub version 1.4.2 Index]