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Multiple Testing Genewise Across Contrasts

Source: R/fitMixedModelDE.R
classifyTestsF-MArrayLM2-method.Rd

For each gene, classify a series of related t-statistics as up, down or not significant.

Usage

# S4 method for class 'MArrayLM2'
classifyTestsF(
  object,
  cor.matrix = NULL,
  df = Inf,
  p.value = 0.01,
  fstat.only = FALSE
)

Arguments

object

numeric matrix of t-statistics or an 'MArrayLM2' object from which the t-statistics may be extracted.

cor.matrix

covariance matrix of each row of t-statistics. Defaults to the identity matrix.

df

numeric vector giving the degrees of freedom for the t-statistics. May have length 1 or length equal to the number of rows of tstat.

p.value

numeric value between 0 and 1 giving the desired size of the test

fstat.only

logical, if 'TRUE' then return the overall F-statistic as for 'FStat' instead of classifying the test results

Details

Works like limma::classifyTestsF, except object can have a list of covariance matrices object$cov.coefficients.list, instead of just one in object$cov.coefficients

See also

limma::classifyTestsF