comp.SAM {DEDS} | R Documentation |

`comp.SAM`

returns a function of one argument. This function has a
environment with bindings for a series of arguments (see below). It
accepts a microarray data matrix as its single argument, when
evaluated, computes SAM statistics for each row of the matrix.

comp.SAM(L = NULL, prob = 0.5, B = 200, stat.only = TRUE, verbose = FALSE, deltas, s.step=0.01, alpha.step=0.01, plot.it=FALSE)

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

`prob` |
A numeric variable used to set the fudge factor
s_0 in terms of the percentile of the standard deviations of the
genes. If set as `NULL` , s_0 is calculated using the
algorithm by Tusher et al. (see reference). |

`B` |
The number of permutations. For a complete enumeration,
`B` should be 0 (zero) or any number not less than the total
number of permutations. |

`stat.only` |
A logical variable, if `TRUE` , only statistics
are calculated and returned; if `FALSE` , false discovery rates
(FDRs) for a set of delta(`deltas` ) are
calculated and returned. |

`verbose` |
A logical variable, if `TRUE` , informative mesages
are printed during the computation process. |

`deltas` |
A vector of values for the threshold delta; see
Tusher et al. |

`s.step` |
A numeric variable specifying the size of the moving window
acorss the gene-wise standard deviations for the selection of the
fudge factor s_0. |

`alpha.step` |
A numeric variable specifying the increment of a percentile sequence between 0 and 1, from which the fudge factor will be chosen to minimize the coefficient of variation of statistics. |

`plot.it` |
A logical variable, if `TRUE` , a plot between the
coefficient of variation and the percentile sequence will be made. |

The function returned by `comp.SAM`

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

,
`prob`

, `B`

, `stat.only`

, `verbose`

,
`deltas`

, `s.step`

, `alpha.step`

and `plot.it`

. If
`quantile=NULL`

, the fudge factor *s_0* is calculated as the
percentile of the gene-wise standard deviations that minimizes the
coefficient of variation of the statistics; otherwise *s_0* is set
as the specified percentile of standard deviations. If
`stat.only=T`

, only SAM statistics are returned; otherwise,
permutation will be carried out to calculate the FDRs for a set of
`deltas`

specified and a FDR table will be returned in addition
to the SAM statistics.

`SAM`

returns a function (F) with bindings for a series of arguments.
When `stat.only=T`

, the function F when evaluated returns a
numeric vector of SAM statistics;
When `stat.only=F`

, the function F when evaluated returns
a list of the following components:

`geneOrder` |
Order of genes in terms of differential expression; |

`sam` |
Sorted SAM statistics; |

`fdr.table` |
A matrix with columns: delta, no.significance, no.positive, no.negatvie, FDR(50%), FDR(90%). |

Yuanyuan Xiao, yxiao@itsa.ucsf.edu,

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

Tusher, V.G., Tibshirani, R., and Chu, G. (2001). Significance analysis of microarrays
applied to the ionizing radiation response, *PNAS*, 98,
5116-5121.

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 # two sample test, statistics only sam.fun <- comp.SAM(L) sam.X <- sam.fun(X) # two sample test, FDR sam.fun <- comp.SAM(L, stat.only=FALSE, delta=c(0.1, 0.2, 0.5)) sam.X <- sam.fun(X)

[Package *DEDS* version 1.0.3 Index]