qpAdm_rotation | R Documentation |
Fit qpAdm models based on the rotation strategy described in Harney et al. 2020 (bioRxiv)
qpAdm_rotation(
data,
target,
candidates,
minimize = TRUE,
nsources = 2,
ncores = 1,
fulloutput = FALSE,
params = NULL
)
data |
EIGENSTRAT dataset |
target |
Target population that is modeled as admixed |
candidates |
Potential candidates for sources and outgroups |
minimize |
Test also all possible subsets of outgroups? (default TRUE) |
nsources |
Number of sources to pull from the candidates |
ncores |
Number of CPU cores to utilize for model fitting |
fulloutput |
Report also 'ranks' and 'subsets' analysis from qpAdm in addition to the admixture proportions results? (default FALSE) |
params |
Named list of parameters and their values to be passed to
|
qpAdm list with proportions, ranks and subsets elements (as with a traditional qpAdm run) or just the proportions (determined by the value of the 'fulloutput' argument)
## Not run: # download an example genomic data set and prepare it for analysis
snps <- eigenstrat(download_data(dirname = tempdir()))
# find the set of most likely two-source qpAdm models of
# a French individual - produce only the 'proportions'
# qpAdm summary
models <- qpAdm_rotation(
data = snps,
target = "French",
candidates = c("Dinka", "Mbuti", "Yoruba", "Vindija",
"Altai", "Denisova", "Chimp"),
minimize = TRUE,
nsources = 2,
ncores = 2,
fulloutput = FALSE
)
## End(Not run)
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