z.ebam: EBAM analysis Using t- or F-test

Description Usage Arguments Value Author(s) References See Also


Computes the required statistics for an Empirical Bayes Analysis with a modified t- or F-test.

Should not be called directly, but via ebam(..., method = z.ebam) or find.a0(..., method = z.find), respectively.


  z.ebam(data, cl, a0 = NULL, quan.a0 = NULL, B = 100, var.equal = FALSE, 
      B.more = 0.1, B.max = 30000, n.subset = 10, fast = FALSE, 
      n.interval = 139, df.ratio = NULL, rand = NA)
  z.find(data, cl, B = 100, var.equal = FALSE, B.more = 0.1, 
      B.max = 30000)



a matrix, data frame or ExpressionSet object. Each row of data (or exprs(data)) must correspond to a variable (e.g., a gene), and each column to a sample (i.e.\ observation).


a numeric vector of length ncol(data) containing the class labels of the samples. For details on how cl should be specified, see ebam.


a numeric value specifying the fudge factor.


a numeric value between 0 and 1 specifying the quantile of the standard deviations of the genes that is used as fudge factor.


an integer indicating how many permutations should be used in the estimation of the null distribution.


should the ordinary t-statistic assuming equal group variances be computed? If FALSE (default), Welch's t-statistic will be computed.


a numeric value. If the number of all possible permutations is smaller than or equal to (1+B.more)*B, full permutation will be done. Otherwise, B permutations are used. This avoids that B permutations will be used – and not all permutations – if the number of all possible permutations is just a little larger than B.


a numeric value. If the number of all possible permutations is smaller than or equal to B.max, B randomly selected permutations will be used in the computation of the null distribution. Otherwise, B random draws of the group labels are used. In the latter way of permuting, it is possible that some of the permutations are used more than once.


an integer specifying in how many subsets the B permutations should be split when computing the permuted test scores. Note that the meaning of n.subset differs between the SAM and the EBAM functions.


if FALSE the exact number of permuted test scores that are more extreme than a particular observed test score is computed for each of the genes. If TRUE, a crude estimate of this number is used.


the number of intervals used in the logistic regression with repeated observations for estimating the ratio f0/f.


integer specifying the degrees of freedom of the natural cubic spline used in the logistic regression with repeated observations.


integer. If specified, i.e. not NA, the random number generator will be set into a reproducible state.


A list of object required by find.a0 or ebam, respectively.


Holger Schwender, [email protected]


Efron, B., Tibshirani, R., Storey, J.D. and Tusher, V. (2001). Empirical Bayes Analysis of a Microarray Experiment, JASA, 96, 1151-1160.

Schwender, H., Krause, A. and Ickstadt, K. (2003). Comparison of the Empirical Bayes and the Significance Analysis of Microarrays. Technical Report, SFB 475, University of Dortmund, Germany.

See Also

ebam, find.a0, d.stat

siggenes documentation built on May 2, 2018, 6:07 p.m.