Thresher (version 1.1.3)

SignalSet-class: Class "SignalSet"

Description

We use the term "(continuous) signal" to refer to a weighted sum (by default, the mean) of gene-features. By dichotomizing a continuous signals, we obtain a "binary signal". The SignalSet class represents the set of continuous and binary signals obtained after clustering the features in a data set.

Objects from the Class

Objects can be created by calls of the form new("SignalSet", ...). However, users are styrongly discouraged from contructing a SignalSet manually. They are only used in the code internal to the construction of a Reaper object.

Slots

members:

Object of class "list". Each member of the list is a character vector enumerating the features defining each signal.

continuous:

A matrix where the number of columns equals the length of the members list; each column contains the mean expression of the (assumed standardized) corresponding features.

binary:

A matrix where the number of columns equals the length of the members list; each column contains expression values dichotmoized to 0 or 1 by splitting the conmtinuous siognal at zero.

continuousClusters:

Object of class "hclust" obtained by clustering samples based on the continuous signals.

binaryClusters:

Object of class "hclust" obtained by clustering samples based on the binary signals.

Methods

No methods defined with class "SignalSet" in the signature.

See Also

Reaper

Examples

# NOT RUN {
# Simulate  a data set with some structure
set.seed(250264)
sigma1 <- matrix(0, ncol=16, nrow=16)
sigma1[1:7, 1:7] <- 0.7
sigma1[8:14, 8:14] <- 0.3
diag(sigma1) <- 1
st <- SimThresher(sigma1, nSample=300)
# Threshing is completed; now we can reap
reap <- Reaper(st)
# now extract the signal set
ss <- reap@signalSet
dim(ss@continuous)
dim(ss@binary)
table(ss@binary[,1], ss@binary[,2])
plot(ss@continuousClusters)
# }