tdt {trio} | R Documentation |
Computes the genotypic TDT for a SNP or for each column of a matrix representing a SNP.
tdt(snp, model = c("additive", "dominant", "recessive")) colTDT(mat.snp, model = c("additive", "dominant", "recessive"), size = 50) ## S3 method for class 'tdt' print(x, digits = 4, ...) ## S3 method for class 'colTDT' print(x, top = 5, digits = 4, ...)
snp |
a numeric vector of length 3 * t representing a SNP genotyped at t trios. Each of the t
blocks (i.e. |
mat.snp |
a numeric matrix in which each column represents a SNP. Each of the SNPs must have the same structure
as |
model |
type of model that should be fitted. Abbreviations are allowed. Thus, e.g., |
size |
the number of SNPs considered simultaneously when computing the parameter estimates. Ignored if |
x |
an object of class |
digits |
number of digits that should be printed. |
top |
number of interactions that should be printed. If |
... |
ignored. |
An object of class tdt
or colTDT
consisting of the following numeric values or vectors, respectively:
coef |
the estimated parameter, |
se |
the estimated standard deviation of the parameter estimate, |
stat |
Wald statistic, |
RR |
the relative risk, i.e.\ for trio data, |
lowerRR |
the lower bound of the 95% confidence interval for |
upperRR |
the upper bound of the 95% confidence interval for |
usedTrios |
the number of trios affecting the parameter estimation (only for |
... |
further internal parameters |
Holger Schwender, holger.schwender@udo.edu
Schaid, D.J. (1996). General Score Tests for Associations of Genetic Markers with Disease Using Cases and Their Parents. Genetic Epidemiology, 13, 423-449.
Schwender, H., Taub, M.A., Beaty, T.H., Marazita, M.L., and Ruczinski, I. (2011). Rapid Testing of SNPs and Gene-Environment Interactions in Case-Parent Trio Data Based on Exact Analytic Parameter Estimation. Biometrics, 68, 766-773.
# Load the simulated data. data(trio.data) # One particular SNP (e.g., the one in the first # column of mat.test) can be tested by tdt.out <- tdt(mat.test[,1]) # All SNPs in mat.test can be tested by tdt.out2 <- colTDT(mat.test) # By default, an additive mode of inheritance is considered. # If another mode, e.g., the dominant mode, should be # considered, then this can be done by tdt.out3 <- colTDT(mat.test, model = "dominant") # By default, statistics for the top 5 SNPs are displayed. # If another number of SNPs, say 10, should be displayed, # then this can be done by print(tdt.out2, top = 10) # The statistics for all SNPs (not ordered by their # significance) can be obtained by print(tdt.out2, top = 0)