Description Usage Arguments Details Value Note Author(s) References See Also Examples

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

1 2 3 4 |

`data` |
a matrix, data frame or an ExpressionSet object.
Each row of |

`cl` |
a numeric vector of length In the one-class case, In the two class unpaired case, In the two class paired case, In the multiclass case and if For examples of how |

`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 |

`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 |

`quan.a0` |
a numeric vector indicating over which quantiles of the
standard deviations of the genes the fudge factor |

`include.zero` |
should |

`control` |
further arguments for controlling the EBAM analysis with |

`gene.names` |
a character vector of length |

`rand` |
integer. If specified, i.e. not |

`...` |
further arguments for the function specified by |

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`

.

An object of class FindA0.

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.

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.

`ebam`

, `FindA0-class`

, `find.a0Control`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | ```
## 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)
``` |

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