classifyTestsF,MArrayLM2-method {variancePartition} | R Documentation

## Multiple Testing Genewise Across Contrasts

### Description

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

### Usage

    ## S4 method for signature '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

[Package variancePartition version 1.17.10 Index]