mlg: Create counts, vectors, and matrices of multilocus genotypes.

Description

Create counts, vectors, and matrices of multilocus genotypes.

Usage

mlg(pop, quiet = FALSE)
mlg.table(pop, sublist = "ALL", blacklist = NULL, mlgsub = NULL,
  bar = TRUE, total = FALSE, quiet = FALSE)
mlg.vector(pop)
mlg.crosspop(pop, sublist = "ALL", blacklist = NULL, mlgsub = NULL,
  indexreturn = FALSE, df = FALSE, quiet = FALSE)
mlg.id(pop)

Arguments

pop

a genind or genclone object.

quiet

Logical. If FALSE, progress of functions will be printed to the screen.

sublist

a vector of population names or indices that the user wishes to keep. Default to "ALL".

blacklist

a vector of population names or indices that the user wishes to discard. Default to NULL.

mlgsub

a vector of multilocus genotype indices with which to subset mlg.table and mlg.crosspop. NOTE: The resulting table from mlg.table will only contain countries with those MLGs

bar

logical If TRUE, a bar graph for each population will be displayed showing the relative abundance of each MLG within the population.

total

logical If TRUE, a row containing the sum of all represented MLGs is appended to the matrix produced by mlg.table.

indexreturn

logical If TRUE, a vector will be returned to index the columns of mlg.table.

logical If TRUE, return a data frame containing the counts of the MLGs and what countries they are in. Useful for making graphs with ggplot.

Value

mlg{ an integer describing the number of multilocus genotypes observed. } mlg.table{ a matrix with columns indicating unique multilocus genotypes and rows indicating populations. } mlg.vector{ a numeric vector naming the multilocus genotype of each individual in the dataset. } mlg.crosspop{
- default
{ a list where each element contains a named integer vector representing the number of individuals represented from each population in that MLG}
indexreturn = TRUEa vector of integers defining the multilocus genotypes that have individuals crossing populations
df = TRUEA long form data frame with the columns: MLG, Population, Count. Useful for graphing with ggplot2
}

subsection

mlg.id

Examples

Run this code

# Load the data set
data(Aeut)

# Investigate the number of multilocus genotypes.
amlg <- mlg(Aeut)
amlg # 119

# show the multilocus genotype vector
avec <- mlg.vector(Aeut)
avec

# Get a table
atab <- mlg.table(Aeut, bar = FALSE)
atab

# See where multilocus genotypes cross populations
acrs <- mlg.crosspop(Aeut) # MLG.59: (2 inds) Athena Mt. Vernon

# See which individuals belong to each MLG
aid <- mlg.id(Aeut)
aid["59"] # individuals 159 and 57

# A simple example. 10 individuals, 5 genotypes.
mat1 <- matrix(ncol=5, 25:1)
mat1 <- rbind(mat1, mat1)
mat <- matrix(nrow=10, ncol=5, paste(mat1,mat1,sep="/"))
mat.gid <- df2genind(mat, sep="/")
mlg(mat.gid)
mlg.vector(mat.gid)
mlg.table(mat.gid)

# Now for a more complicated example.
# Data set of 1903 samples of the H3N2 flu virus genotyped at 125 SNP loci.
data(H3N2)
mlg(H3N2, quiet=FALSE)

H.vec <- mlg.vector(H3N2)

# Changing the population vector to indicate the years of each epidemic.
pop(H3N2) <- other(H3N2)$x$country
H.tab <- mlg.table(H3N2, bar=FALSE, total=TRUE)

# Show which genotypes exist accross populations in the entire dataset.
res <- mlg.crosspop(H3N2, quiet=FALSE)

# Let's say we want to visualize the multilocus genotype distribution for the
# USA and Russia
mlg.table(H3N2, sublist=c("USA", "Russia"), bar=TRUE)

# An exercise in subsetting the output of mlg.table and mlg.vector.
# First, get the indices of each MLG duplicated across populations.
inds <- mlg.crosspop(H3N2, quiet=FALSE, indexreturn=TRUE)

# Since the columns of the table from mlg.table are equal to the number of
# MLGs, we can subset with just the columns.
H.sub <- H.tab[, inds]

# We can also do the same by using the mlgsub flag.
H.sub <- mlg.table(H3N2, mlgsub=inds)

# We can subset the original data set using the output of mlg.vector to
# analyze only the MLGs that are duplicated across populations.
new.H <- H3N2[H.vec %in% inds, ]