rowTrendFuzzy {scrime} | R Documentation |
Trend Test for Fuzzy Genotype Calls
Description
rowTrendFuzzy
performs the trend test proposed by Louis et al. (2010) based on fuzzy genotype calls, i.e. the weighted sums
over the confidences for the three genotypes as they are determined by preprocessing algorithms (e.g., CRLMM)
or imputation procedures.
Given the confidences and scores for all three genotypes, getMatFuzzy
constructs a matrix containing the fuzzy genotype calls.
Usage
rowTrendFuzzy(score, probs, y, mat.fuzzy = NULL,
alternative = c("two.sided", "less", "greater"),
check = TRUE)
getMatFuzzy(score, probs, check = TRUE)
Arguments
score |
either a numeric vector of length 2 or 3, or a character string. If the latter, If |
probs |
a list of length 2 or 3 consisting of matrices of the same size. Each matrix must contain the confidences
for one of the three genotypes, where each row in the matrix represents a SNP and each column a sample (which must be in the same
order in all matrices). The matrices in |
y |
a vector of zeros and ones specifying which of the samples in the matrices in |
mat.fuzzy |
a matrix containing the fuzzy genotype calls. If specified, |
alternative |
a character string specifying the alternative hypothesis. Must be one of |
check |
logical specifying whether the specified objects should be extensively checked. If |
Value
For getMatFuzzy
, a matrix containing the fuzzy genotype calls. For rowTrendFuzzy
, a list consisting of
stat |
a vector containing the values of the trend test statistic for all SNPs comprised by |
rawp |
a vector containing the unadjusted p-values computed for the values in |
theta |
a vector containing estimates for the log odds ratios for risk corresponding to |
varTheta |
a vector containing the variance estimates for |
References
Louis, T.A., Carvalho, B.S., Fallin, M.D., Irizarry, R.A., Li, Q., and Ruczinski, I. (2010). Association Tests that Accommodate Genotyping Errors. In Bernardo, J.M., Bayarri, M.J., Berger, J.O., Dawid, A.P., Heckerman, D., Smith, A.F.M., and West, M. (eds.), Bayesian Statistics 9, 393-420. Oxford University Press, Oxford, UK. With Discussion.