grm.matrix: GRM for multiple individuals
In rres: Realized Relatedness Estimation and Simulation
Description
Usage
Arguments
Details
References
See Also
Description
grm.matrix computes relatedness estimates between every pairs of individuals.
Usage
1
2
grm.matrix(genotype, freq, method = "twostep", weights = NULL,
init.est = NULL)
Arguments
genotype
numeric matrix.
freq
numeric vector, values between 0 and 1.
method
string.
weights
numeric vector, values between 0 and 1.
init.est
numeric.
Details
genotype is the matrix of counts of reference alleles. Rows represents subjects and columns represents SNP markers. freq is the vector of reference allele frequencies.
The default method is "twostep", other options include "classic", "robust" and "general". When using the default "twostep" method, user can supply an initial estimate through init.est to bypass the first step. When "general" is selected, weights must also be specified. The difference between the two-step GRM, classic GRM and robust GRM is discussed in Wang et al. (2017).
References
Wang et al. (2017) Genetics 205:1063-1078, https://www.ncbi.nlm.nih.gov/pubmed/28100587.
See Also
rres documentation built on May 2, 2019, 2:51 p.m.
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Description Usage Arguments Details References See Also
Description
grm.matrix computes relatedness estimates between every pairs of individuals.
Usage
1 2 | grm.matrix(genotype, freq, method = "twostep", weights = NULL,
init.est = NULL)
|
Arguments
genotype |
numeric matrix. |
freq |
numeric vector, values between 0 and 1. |
method |
string. |
weights |
numeric vector, values between 0 and 1. |
init.est |
numeric. |
Details
genotype is the matrix of counts of reference alleles. Rows represents subjects and columns represents SNP markers. freq is the vector of reference allele frequencies.
The default method is "twostep", other options include "classic", "robust" and "general". When using the default "twostep" method, user can supply an initial estimate through init.est to bypass the first step. When "general" is selected, weights must also be specified. The difference between the two-step GRM, classic GRM and robust GRM is discussed in Wang et al. (2017).
References
Wang et al. (2017) Genetics 205:1063-1078, https://www.ncbi.nlm.nih.gov/pubmed/28100587.
See Also
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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