comp.B {DEDS} | R Documentation |

## Computing B-statistics for Differential Expression

### Description

`comp.B`

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

and `proportion`

. This function accepts a microarray
data matrix as its single argment, when evaluated, computes lod-odds
of differential expression by emprical Bayes shrinkage of the standard
error toward a common value. The lod-odds are sometimes called B
statistics.

### Usage

comp.B(L = NULL, proportion = 0.01)

### 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*. |

`proportion` |
A numeric variable specifying the proportion of
differential expression. |

### Details

The function returned by `comp.B`

calculates B statistics for
each row of the microarray data matrix, with bindings for `L`

and
`proportion`

. It interfaces to a C function. `comp.stat`

is another function that wrapps around the same C function that could
be used for computing B statistics (see examples below).

### Value

`comp.B`

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

and `proportion`

. The function F when supplied with
a microarray data matrix and evaluated will return a numeric vector of
B 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.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
# compute B statistics, proportion set as 0.01
B.fun <- comp.B(L)
B.X <- B.fun(X)
# compute B statistics, proportion set as 0.1
B.fun <- comp.B(L, proportion=0.1)
B.X <- B.fun(X)
# Another way of computing B statistics
B.X<- comp.stat(X, L, "B")

[Package

*DEDS* version 1.0.3

Index]