GCTA_singleValue {modACDC} | R Documentation |
GCTA_singleValue
Description
Function to return the heritability of an external phenotype for a single dataset
Usage
GCTA_singleValue(
fileLoc,
externalVar,
gctaPath,
remlAlg = 0,
maxRemlIt = 100,
numCovars = NULL,
catCovars = NULL
)
Arguments
fileLoc |
absolute file path to bed, bim, and fam files, including prefix |
externalVar |
vector of length n of external variable values with no ID column; must be in the same sample order as bed, bim, fam files |
gctaPath |
absolute path to GCTA software |
remlAlg |
algorithm to run REML iterations in GCTA; 0 = average information (AI), 1 = Fisher-scoring, 2 = EM; default is 0 (AI) |
maxRemlIt |
the maximum number of REML iterations; default is 100 |
numCovars |
n x c_n matrix of numerical covariates to adjust heritability model for; must be in same person order as fam file; default is NULL |
catCovars |
n x c_c matrix of categorical covariates to adjust heritability model for; must be in same person order as fam file; default is NULL |
Details
Genome-wide Complex Trait Analysis (GCTA) is a suite of C++ functions. In order to use the GCTA functions, the user must specify the absolute path to the GCTA software, which can be downloaded from the Yang Lab website here.
Here, we use GCTA's Genomics REstricted Maximum Likelihood (GREML) method to estimate the heritability of an external phenotype.
Value
Row of GREML output containing heritability point estimate of external data and standard error
Author(s)
Katelyn Queen, kjqueen@usc.edu
References
Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet. 2011 Jan 7;88(1):76-82. doi: 10.1016/j.ajhg.2010.11.011. Epub 2010 Dec 17. PMID: 21167468; PMCID: PMC3014363.
See Also
GCTA software - https://yanglab.westlake.edu.cn/software/gcta/
Examples
externalVar <- c()
# run function; input data before running
## Not run: OSCA_singleValue(fileLoc = "pathHere",
externalVar = externalVar,
gctaPath = "pathHere")
## End(Not run)