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)