lazadm: Estimate admixture weights

In uqrmaie1/admixtools: Inferring demographic history from genetic data

Estimate admixture weights

Description

Models target as a mixture of left populations, and outgroup right populations. Uses Lazaridis method based non-negative least squares of f4 matrix.

Usage

lazadm(data, left, right, target, boot = FALSE, constrained = TRUE)

Arguments

data	The input data in the form of: A 3d array of blocked f2 statistics, output of f2_from_precomp or extract_f2 A directory with f2 statistics The prefix of a genotype file
left	Left populations (sources)
right	Right populations (outgroups)
target	Target population
boot	If FALSE (the default), block-jackknife resampling will be used to compute standard errors. Otherwise, block-bootstrap resampling will be used to compute standard errors. If boot is an integer, that number will specify the number of bootstrap resamplings. If boot = TRUE, the number of bootstrap resamplings will be equal to the number of SNP blocks.
constrained	Constrain admixture weights to be non-negative

Value

lazadm returns a data frame with weights and standard errors for each left population

References

Patterson, N. et al. (2012) Ancient admixture in human history. Genetics

Haak, W. et al. (2015) Massive migration from the steppe was a source for Indo-European languages in Europe. Nature (SI 9)

See Also

qpadm

Examples

target = 'Denisova.DG'
left = c('Altai_Neanderthal.DG', 'Vindija.DG')
right = c('Chimp.REF', 'Mbuti.DG', 'Russia_Ust_Ishim.DG', 'Switzerland_Bichon.SG')
lazadm(example_f2_blocks, left, right, target)
lazadm(example_f2_blocks, left, right, target, constrained = FALSE)

uqrmaie1/admixtools documentation built on April 25, 2024, 11:30 a.m.