comp.modF {DEDS} | R Documentation |

## Computing Moderated t-statistics for Differential Expression

### Description

`comp.modF`

returns a function of one argument with bindings for
`L`

. The function accepts a microarray data matrix as its single
argument, when evaluated, computes moderated F-statistics by emprical
Bayes shrinkage of the standard error toward a common value.

### Usage

comp.modF(L = NULL)

### Arguments

`L` |
A vector of integers corresponding to observation (column)
class labels. For *k* classes, the labels must be integers
between 0 and *k-1*. |

### Details

The function returned by `comp.modF`

computes moderated F
statistics for the assessment of differential expression. It
interfaces to a C function. `comp.stat`

is another
function that wrapps around the C function that could be used for
computing moderated F statistics. For details of moderated statistics,
see Smyth (2003).

### Value

`comp.modF`

returns a function (F) with the bindings for
`L`

. The function F when supplied with a microarray data matrix
and evaluated will return a numeric vector of moderated F statistics
for each row of the matrix.

### Author(s)

Yuanyuan Xiao, yxiao@itsa.ucsf.edu,

Jean Yee Hwa Yang, jean@biostat.ucsf.edu.

### References

Lönnstedt, I. and Speed, T. P. (2002). Replicated microarray
data. *Statistica Sinica* **12**, 31-46.

Smyth, G. K. (2003). Linear models and empirical Bayes methods for
assessing differential expression in microarray
experiments. http://www.statsci.org/smyth/pubs/ebayes.pdf

### See Also

`comp.FC`

, `comp.modt`

, `comp.stat`

### Examples

X <- matrix(rnorm(1000,0,0.5), nc=10)
L <- rep(0:1,c(5,5))
# genes 1-10 are differentially expressed
X[1:10,6:10]<-X[1:10,6:10]+1
fmod <- comp.modF(L)
fmod.X <- fmod(X)
# Another way of computing moderated F statistics
fmod.X <- comp.stat(X, L, "modf")

[Package

*DEDS* version 1.0.3

Index]