find.a0 {siggenes} | R Documentation

## Computation of the Fudge Factor

### Description

Suggests an optimal value for the fudge factor in an EBAM analysis as proposed by Efron et al. (2001).

### Usage

      find.a0(data, cl, method = z.find, B = 100, delta = 0.9,
          quan.a0 = (0:5)/5, include.zero = TRUE,
          control = find.a0Control(), gene.names = dimnames(data)[[1]],
          rand = NA, ...)

### Arguments

`data` | a matrix, data frame or an ExpressionSet object. Each row of `data` (or `exprs(data)`, respectively) must correspond to a variable (e.g., a gene), and each column to a sample (i.e.\ an observation).
`cl` | a numeric vector of length `ncol(data)` containing the class labels of the samples. In the two class paired case, `cl` can also be a matrix with `ncol(data)` rows and 2 columns. If `data` is an ExpressionSet object, `cl` can also be a character string naming the column of `pData(data)` that contains the class labels of the samples. In the one-class case, `cl` should be a vector of 1's. In the two class unpaired case, `cl` should be a vector containing 0's (specifying the samples of, e.g., the control group) and 1's (specifying, e.g., the case group). In the two class paired case, `cl` can be either a numeric vector or a numeric matrix. If it is a vector, then `cl` has to consist of the integers between -1 and -n/2 (e.g., before treatment group) and between 1 and n/2 (e.g., after treatment group), where n is the length of `cl` and k is paired with -k, k=1,…,n/2. If `cl` is a matrix, one column should contain -1's and 1's specifying, e.g., the before and the after treatment samples, respectively, and the other column should contain integer between 1 and n/2 specifying the n/2 pairs of observations. In the multiclass case and if `method = cat.stat`, `cl` should be a vector containing integers between 1 and g, where g is the number of groups. For examples of how `cl` can be specified, see the manual of siggenes.
`method` | the name of a function for computing the numerator and the denominator of the test statistic of interest, and for specifying other objects required for the identification of the fudge factor. The default function `z.find` provides these objects for t- and F-statistics. It is, however, also possible to employ an user-written function. For how to write such a function, see the vignette of siggenes.
`B` | the number of permutations used in the estimation of the null distribution.
`delta` | a probability. All genes showing a posterior probability that is larger than or equal to `delta` are called differentially expressed.
`quan.a0` | a numeric vector indicating over which quantiles of the standard deviations of the genes the fudge factor a0 should be optimized.
`include.zero` | should a0 = 0, i.e. the not-modified test statistic also be a possible choice for the fudge factor?
`control` | further arguments for controlling the EBAM analysis with `find.a0`. For these arguments, see `find.a0Control`.
`gene.names` | a character vector of length `nrow(data)` containing the names of the genes. By default, the row names of `data` are used.
`rand` | integer. If specified, i.e. not `NA`, the random number generator will be set into a reproducible state.
`...` | further arguments for the function specified by `fun`. For further arguments of `fun = z.find`, see `z.find`.

### Details

The suggested choice for the fudge factor is the value of a0 that leads to the largest number of genes showing a posterior probability larger than `delta`.

Actually, only the genes having a posterior probability larger than `delta` are called differentially expressed that do not exhibit a test score less extreme than the score of a gene whose posterior probability is less than `delta`. So, let's say, we have done an EBAM analysis with a t-test and we have ordered the genes by their t-statistic. Let's further assume that Gene 1 to Gene 5 (i.e. the five genes with the lowest t-statistics), Gene 7 and 8, Gene 3012 to 3020, and Gene 3040 to 3051 are the only genes that show a posterior probability larger than `delta`. Then, Gene 1 to 5, and 3040 to 3051 are called differentially expressed, but Gene 7 and 8, and 3012 to 3020 are not called differentially expressed, since Gene 6 and Gene 3021 to 3039 show a posterior probability less than `delta`.

### Value

An object of class FindA0.

### Note

The numbers of differentially expressed genes can differ between `find.a0` and `ebam`, even though the same value of the fudge factor is used, since in `find.a0` the observed and permuted test scores are monotonically transformed such that the observed scores follow a standard normal distribution (if the test statistic can take both positive and negative values) and an F-distribution (if the test statistic can only take positive values) for each possible choice of the fudge factor.

### Author(s)

Holger Schwender, holger.schw@gmx.de

### References

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

### See Also

`ebam`, `FindA0-class`, `find.a0Control`

### Examples

    ## Not run:
      # Load the data of Golub et al. (1999) contained in the package multtest.
      data(golub)

      # golub.cl contains the class labels.
      golub.cl

      # Obtain the number of differentially expressed genes and the FDR for the
      # default set of values for the fudge factor.
      find.out <- find.a0(golub, golub.cl, rand = 123)
      find.out

      # Obtain the number of differentially expressed genes and the FDR when using
      # the t-statistic assuming equal group variances
      find.out2 <- find.a0(golub, golub.cl, var.equal = TRUE, rand = 123)

      # Using the Output of the first analysis with find.a0, the number of
      # differentially expressed genes and the FDR for other values of
      # delta, e.g., 0.95, can be obtained by
      print(find.out, 0.95)

      # The logit-transformed posterior probabilities can be plotted by
      plot(find.out)

      # To avoid the logit-transformation, set logit = FALSE.
      plot(find.out, logit = FALSE)

    ## End(Not run)

[Package siggenes version 1.62.0 Index]