Description Usage Arguments Value Author(s)
View source: R/NormalizedASKAT.region.R
Runs the normalized ASKAT method on a given genomic region. Rankbased normalization is applied to the phenotype residauls under the null model, after adjusting for covariate effects
1 2 3 4 
y 
vector of phenotype data (one entry per individual), of length n. 
X 
matrix of covariates including intercept (dimension: n \times p, with p the number of covariates) 
Phi 
Relationship matrix (i.e. twice the kinship matrix); an n \times n square symmetric positivedefinite matrix. 
type 
character, 
filename 
character, path to input file containing haplotype data 
map 
object, data.frame contains 3 columns: rsID, chromosome,
position in bp as output by e.g. 
chr 
character, chromosome number (basically from 1 to 22 as used by Plink), on which the region of interest is located 
startpos 
numeric, start position (in bp, base pairs) of the region of interest (default: 0) 
endpos 
numeric, end position (in bp, base pairs) of the region of interest (default: 0) 
regionname 
(character) Name of the region/gene on which you are running the association test. This name is used in the output of this function and can be used to distinguish different regions if this function is run multiple times. 
U 
(optional) Matrix of Eigenvectors of the relationship matrix
obtained from spectral decomposition of the relationship matrix:
Φ = U S U^T. If this parameter is not given, it will
be computed, so when running this function for many regions
time can be saved by specifying not only 
S 
(optional) Matrix of Eigenvalues of the relationship matrix
obtained from spectral decomposition of the relationship matrix:
Φ = U S U^T. If this parameter is not given, it will
be computed, so when running this function for many regions,
time can be saved by specifying not only 
RH.Null 
(optional) output of

weights 
optional numeric vector of genotype weights. If
this option is not specified, the beta distribution is used
for weighting the variants, with each weight given by
w_i = dbeta(f_i, 1, 25)^2, with f_i the minor
allele frequency (MAF) of variant i. This default is the
same as used by the

A data frame containing the results of the association test. The data frame contains the following columns:
Score.Test
: the score of the given association test
P.value
: the pvalue of the association test
N.Markers
: the number of markers in the region
regionname
: Name of the region/gene on which you
are running the association test
Lennart C. Karssen, Sodbo Sharapov
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