snpgdsIndInb | R Documentation |
To calculate individual inbreeding coefficients using SNP genotype data
snpgdsIndInb(gdsobj, sample.id=NULL, snp.id=NULL,
autosome.only=TRUE, remove.monosnp=TRUE, maf=NaN, missing.rate=NaN,
method=c("mom.weir", "mom.visscher", "mle", "gcta1", "gcta2", "gcta3"),
allele.freq=NULL, out.num.iter=TRUE, reltol=.Machine$double.eps^0.75,
verbose=TRUE)
gdsobj |
an object of class |
sample.id |
a vector of sample id specifying selected samples; if NULL, all samples are used |
snp.id |
a vector of snp id specifying selected SNPs; if NULL, all SNPs are used |
autosome.only |
if |
remove.monosnp |
if TRUE, remove monomorphic SNPs |
maf |
to use the SNPs with ">= maf" only; if NaN, no MAF threshold |
missing.rate |
to use the SNPs with "<= missing.rate" only; if NaN, no missing threshold |
method |
see details |
allele.freq |
to specify the allele frequencies; if NULL, the allele frequencies are estimated from the given samples |
out.num.iter |
output the numbers of iterations |
reltol |
relative convergence tolerance used in MLE; the algorithm stops if it is unable to reduce the value of log likelihood by a factor of $reltol * (abs(log likelihood with the initial parameters) + reltol)$ at a step. |
verbose |
if TRUE, show information |
The method
can be:
"mom.weir": a modified Visscher's estimator, proposed by Bruce Weir;
"mom.visscher": Visscher's estimator described in Yang et al. (2010);
"mle": the maximum likelihood estimation;
"gcta1": F^I in GCTA, avg [(g_i - 2p_i)^2 / (2*p_i*(1-p_i)) - 1];
"gcta2": F^II in GCTA, avg [1 - g_i*(2 - g_i) / (2*p_i*(1-p_i))];
"gcta3": F^III in GCTA, the same as "mom.visscher",
avg [g_i^2 - (1 + 2p_i)*g_i + 2*p_i^2] / (2*p_i*(1-p_i)).
Return estimated inbreeding coefficient.
Xiuwen Zheng
Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, Madden PA, Heath AC, Martin NG, Montgomery GW, Goddard ME, Visscher PM. 2010. Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 42(7):565-9. Epub 2010 Jun 20.
Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. GCTA: a tool for genome-wide complex trait analysis. American journal of human genetics 88, 76-82 (2011).
# open an example dataset (HapMap)
genofile <- snpgdsOpen(snpgdsExampleFileName())
rv <- snpgdsIndInb(genofile, method="mom.visscher")
head(rv$inbreeding)
summary(rv$inbreeding)
# close the genotype file
snpgdsClose(genofile)
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