Description Usage Arguments Value Author(s) See Also Examples
Performs score tests for all individual SNPs (scoreTDT
), all interactions of each SNP with an environmental variable (scoreGxE
),
or all interactions of two SNPs (scoreGxG
) comprised by an input matrix based on the same loglikelihood considered in the corresponding
genotypic TDT, where in scoreGxG
the conditional logistic regression model including only one parameter (for the interaction effect)
is used.
Additionally, the maximum over the score statistics for testing an additive, dominant, and recessive effect can be
determined using scoreMaxStat
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18  scoreTDT(mat.snp, model = c("additive", "dominant", "recessive"), size = 20)
scoreGxE(mat.snp, env, model = c("additive", "dominant", "recessive"), size = 20,
famid = NULL)
scoreGxG(mat.snp, model = c("additive", "dominant", "recessive"), genes = NULL,
size = 20)
scoreMaxStat(mat.snp, size = 20)
## S3 method for class 'scoreTDT'
print(x, top = 5, digits = 4, ...)
## S3 method for class 'scoreGxE'
print(x, top = 5, digits = 4, onlyGxE = FALSE, ...)
## S3 method for class 'maxScoreTrio'
print(x, top = 5, digits = 4, ...)

mat.snp 
a numeric matrix in which each column represents a SNP. Each column must be
a numeric vector of length 3 * t representing a SNP genotyped at t trios. Each of the t
blocks must consist of the genotypes of father, mother, and offspring
(in this order). The genotypes must be coded by 0, 1, and 2. Missing values are allowed and need to be coded by 
model 
type of model that should be fitted. Abbreviations are allowed. Thus, e.g., 
size 
the number of models considered simultaneously when computing the parameter estimates. 
env 
a vector of length t (see 
famid 
a vector of the same length as 
genes 
a character vector containing the names of the genes (or LDblocks or other genetic sets of SNPs) to which the SNPs belong.
If specified, only the twoway interactions between SNPs from different genes (or LDblocks or other genetic sets of SNPs) are tested.
If 
x 
an object of class 
digits 
number of digits that should be printed. 
top 
number of interactions that should be printed. If the number of interactions is smaller than or equal to

onlyGxE 
logical indicating whether only the statistics for the parameter of the GxE interaction should be printed.
If 
... 
ignored. 
For scoreTDT
and scoreGxG
, an object of class scoreTDT
containing numeric vectors
score 
the scores for all SNPs or SNP interactions, 
info 
the denominators of the corresponding score statistics 
,
stat 
the values of the score statistics for all SNPs or SNP interactions 
,
pval 
the corresponding pvalues computed based on a ChiSquaredistribution with 1 degree of freedom. 
Holger Schwender, holger.schwender@udo.edu
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31  # Load the simulated data.
data(trio.data)
# A score test can be applied to the SNPs in
# mat.test by
s.out < scoreTDT(mat.test)
# By default, an additive mode of inheritance is considered.
# Another mode, e.g., the dominant mode can be considered by
sDom.out < scoreTDT(mat.test, model = "dominant")
# The test statistic of the MAX score test can be computed by
sMax.out < scoreMaxStat(mat.test)
# The interaction between a binary environmental factor,
# e.g., the gender, and each SNP in mat.test can be tested
# by setting up the vector containing the value of the
# environmental factor for each trio. If we, e.g., assume
# that the children in the first 50 trios are girls
# and in the remaininge 50 trios boys, then this vector
# can be generated by
sex < rep(0:1, each = 50)
# and the interaction between sex and each SNP in mat.test
# can be tested with a score test by
sgxe.out < scoreGxE(mat.test, sex)
# The interactions between all pairs of SNPs in mat.test
# can be tested with a score test by
sgxg.out < scoreGxG(mat.test)

Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.