stat.t2 {sma} | R Documentation |
Computes two-sample t-statistics for each gene in a multi-slide microarray experiment.
stat.t2(X, cl, x.ratio=FALSE, var.equal=TRUE, ...)
X |
if x.ratio=F, X is a list containing two components. The
first component is a matrix of log intensity ratios
M=log_2 (R/G) and the second component is the
average log intensities A =
log_2(R*G)/2, such as the output
from stat.ma . If x.ratio=T, X is a matrix of log
expression ratios only. The rows of X correspond to genes and
columns correspond to different hybridizations, that is different
slides. |
cl |
vector of class labels. Must consist of integers 1 and 2. |
x.ratio |
logical flag: if TRUE, the matrix X contains only log intensity ratios, if FALSE, X is a list containing two components. The first component is a matrix of log expression ratios and the second component contains average log intensities A. |
var.equal |
logical flag: if TRUE, the variances of the class 1 and class 2 parent populations are assumed equal. |
... |
other parameters used in t.test . |
List containing the following components
t |
the two-sample t-statistic for each gene; |
Num |
the numerator of the t-statistic for each gene, with names attribute "Num"; |
Denominator |
the denominator of the t-statistic for each gene, with names attribute "Den"; |
n1 |
number of class 1 observations used to calculate the t-statistic for each gene; |
n2 |
number of class 2 observations used to calculate the t-statistics for each gene; |
Average A |
if x.ratio=F, the average across all hybridizations of A = log_2(R*G)/2, with names attribute "A.bar", if x.ratio=T, NULL is returned. |
t2stat.func
is called by stat.t2
and is not typically used on its own.
Sandrine Dudoit, sandrine@stat.berkeley.edu
Yee Hwa Yang, yeehwa@stat.berkeley.edu
D. Freedman, R. Pisani, and R. Purves. (1998). Statistics, 3rd ed. NewYork: W.W. Norton.
t2stat.func
, plot.t2
,
plot.qq
, t.test
.
data(MouseArray) ## mouse.setup <- init.grid() ## mouse.data <- init.data() ## see \emph{init.data} ## mouse.lratio <- stat.ma(mouse.data, mouse.setup) cl <- c(rep(1,3), rep(2,3)) mouse.t2 <- stat.t2(mouse.lratio, cl)