simfam (version 1.1.6)

simfam-package: Simulate and Model Family Pedigrees With Structured Founders

Description

The simfam package is for constructing large random families---with population studies in mind---with realistic constraints including avoidance of close relative pairings but otherwise biased for closest pairs in a 1-dimensional geography. There is also code to draw genotypes across the pedigree starting from genotypes for the founders. Our model allows for the founders to be related or structured---which arises in practice when there are different ancestries among founders---and given known parameters for these founders, we provide code to calculate the true kinship and expected admixture proportions of all descendants.

Author

Maintainer: Alejandro Ochoa (ORCID)

See Also

Useful links:

• https://github.com/OchoaLab/simfam

• Report bugs at https://github.com/OchoaLab/simfam/issues

Examples

# create some toy data for examples
# data dimensions
n <- 10 # number of individuals per generation
G <- 3 # number of generations
m <- 100 # number of loci
K <- 3 # number of ancestries

# start by simulating pedigree
data <- sim_pedigree( n, G )
# creates FAM table (describes pedigree, most important!)
fam <- data$fam
# lists of IDs split by generation
ids <- data$ids
# and local kinship of last generation
kinship_local_G <- data$kinship_local

# prune pedigree to speed up simulations/etc by removing individuals without
# descendants among set of individuals (here it's last generation)
fam <- prune_fam( fam, ids[[ G ]] )

# to model descendants, first need to setup founders with dummy toy data
# 1) random genotypes
X_1 <- matrix( rbinom( n*m, 2, 0.5 ), m, n )
colnames( X_1 ) <- ids[[ 1 ]] # need IDs to match founders
# 2) kinship of unrelated/outbred individuals
# (but in practice can be any structure!)
kinship_1 <- diag( n ) / 2
colnames( kinship_1 ) <- ids[[ 1 ]] # need IDs to match founders
rownames( kinship_1 ) <- ids[[ 1 ]] # ditto
# 3) construct dummy admixture proportions
admix_proportions_1 <- matrix( runif( n * K ), n, K )
# normalize so rows sum to 1
admix_proportions_1 <- admix_proportions_1 / rowSums( admix_proportions_1 )
rownames( admix_proportions_1 ) <- ids[[ 1 ]] # need IDs to match founders

# now construct/draw/propagate information across the pedigree!

# 1) draw genotypes through pedigree, starting from founders!
X <- geno_fam( X_1, fam )
# version for last generation only, which uses less memory
X_G <- geno_last_gen( X_1, fam, ids )

# 2) calculate kinship through pedigree, starting from kinship of founders!
kinship <- kinship_fam( kinship_1, fam )
# version for last generation only, which uses less memory
kinship_G <- kinship_last_gen( kinship_1, fam, ids )

# 3) calculate expected admixture proportions through pedigree, starting from admixture of founders!
admix_proportions <- admix_fam( admix_proportions_1, fam )
# version for last generation only, which uses less memory
admix_proportions_G <- admix_last_gen( admix_proportions_1, fam, ids )