View source: R/betas_estimator.R
betas_estimator | R Documentation |
\beta
s per populationEstimate \beta
s per population.
betas_estimator(data, strata = NULL, filename = NULL, verbose = FALSE)
data |
14 options for input (diploid data only): VCFs (SNPs or Haplotypes,
to make the vcf population ready),
plink (tped, bed), stacks haplotype file, genind (library(adegenet)),
genlight (library(adegenet)), gtypes (library(strataG)), genepop, DArT,
and a data frame in long/tidy or wide format. To verify that radiator detect
your file format use DArT and VCF data: radiator was not meant to generate alleles and genotypes if you are using a VCF file with no genotype (only genotype likelihood: GL or PL). Neither is radiator able to magically generate a genind object from a SilicoDArT dataset. Please look at the first few lines of your dataset to understand it's limit before asking raditor to convert or filter your dataset. |
strata |
(optional)
The strata file is a tab delimited file with a minimum of 2 columns headers:
|
filename |
(optional) The function uses |
verbose |
(optional, logical) When |
A list is created with 3 objects:
betaiovl: Average \beta_i
over loci,
Hw: Within population gene diversities
Hb: Between populations gene diversities
Thierry Gosselin thierrygosselin@icloud.com
Weir, B., Goudet, J. (2017). A Unified Characterization of Population Structure and Relatedness Genetics 206(4), 2085-2103. https://dx.doi.org/10.1534/genetics.116.198424
Goudet, J., Kay, T., Weir, B. (2018). How to estimate kinship Molecular Ecology 27(20), 4121-4135. https://dx.doi.org/10.1111/mec.14833
## Not run:
# Using a VCF file, the simplest for of the function:
fh <- ibdg_fh(
data = "batch_1.vcf",
strata = "strata.panda.tsv"
)
# To see what's inside the list
names(fh)
# To view the manhattan plot:
fh$fh.manhattan.plot
# To view the distribution of FH values:
fh$fh.distribution.plot
## End(Not run)
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