Description Objects from the Class Slots Methods Author(s) See Also Examples
This class is used to represent the results of genetic measurements of the occurence of subsets of a given set of genetic events in a group of patients. Each observation is a binary vector that indicates which events occured in a specific patient. The length of the vector equals the size of the set of genetic events that is taken into consideration.
Objects can be created by calls of the form new("RtreemixData",
Sample, Patients, Events, Description, File)
.
The RtreemixData
class represents patterns of occurences of subsets of
a given set of genetic events in a specific group of patients. The
patterns are given as binary vectors with length equal to the size of
the set of genetic events. In other words, it provides a
representation of the dataset used for learning an mutagenetic trees
mixture model.
The Sample
is a binary matrix
where each row corresponds to the pattern of
genetic events observed in one of the given patients. Hence, the
number of rows gives the number of patients, i.e. the size of the
dataset. Each column corresponds to one of the genetic events.
Missing measurement for the presence or absence of a certain genetic
event in a given pattern is marked with -1. The initial null event
(that initially occurs in all patients) is
not present in the sample, i.e. the first component in each
observation (which is always equal to 1) is left out. This is done for
saving space and avoiding the process of checking for correctly
specified samples.
The Patients
is a character vector
that contains the IDs
of the patients. The length of this vector must be equal to the number
of rows in the Sample
.
The Events
is a character vector
that contains the
labels of the genetic events taken into consideration. Its length
equals one plus the number of columns in the Sample
. This is
because of the label of the null event. When the object of class
RtreemixData
is a parent of a randomly generated
RtreemixModel
object, the events specify the labels of the
genetic events present in the random model, although the Sample
slot
is an empty matrix
. This is because the random mixture models
are not estimated from a given dataset, but generated randomly for
some set of genetic events.
The Description
is a character giving a short description for
the created object.
The File
specifies the path to a text file with a specific
format which contains the infromation needed to create an
RtreemixData
object (the patient IDs, the names of the events,
the matrix with the observations).
Sample
:Object of class "matrix"
.
Patients
:Object of class "character"
. The
Patients
must be of same length as the number of rows in Sample
.
Events
:Object of class "character"
. The length
of Events
must be identical to the number of columns in
Sample
plus one (for specifying the label of the null event).
Description
:Object of class "character"
.
signature(object = "RtreemixData")
: A
method for obtaining the description of the "RtreemixData"
object.
signature(object = "RtreemixData")
: A
method for specifying the Description
of the data object.
signature(object = "RtreemixData")
: A
method for obtaining the labels of the genetic events.
signature(object = "RtreemixData")
: A method
for replacing the names of the genetic events in the data object. It checks
to be sure the values have the right length. As a parent data
of a random RtreemixModel
object the suitable labels of
events present in the model components can be specified although the
Sample
slot is an empty matrix
.
signature(object = "RtreemixData")
: A
method for obtaining the IDs of the patients.
signature(object = "RtreemixData")
: A method
for replacing the IDs of the patients in the data object. It checks
to be sure the values have the right length.
signature(object = "RtreemixData")
: A
method for obtaining the matrix of observations.
signature(object = "RtreemixData")
: A
method for obtaining the number of genetic events.
signature(object = "RtreemixData")
: A
method for obtaining the size of the sample (the number of
patients).
Jasmina Bogojeska
RtreemixGPS-class
, RtreemixStats-class
,
RtreemixModel-class
,
fit-methods
, bootstrap-methods
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ## Create an RtreemixData object from a file given in the examples directory of the package.
data1 <- new("RtreemixData", File = paste(system.file(package = "Rtreemix"), "/examples/treemix.pat", sep = ""))
show(data1) ## show the RtreemixData object
## Create an RtreemixData object from a randomly generated RtreemixModel object.
rand.mod <- generate(K = 3, no.events = 9, noise.tree = TRUE, prob = c(0.2, 0.8))
data2 <- sim(model = rand.mod, no.draws = 300)
show(data2)
## Create an RtreemixData object from a given binary matrix.
bin.mat <- cbind(c(1, 0, 0, 1, 1), c(0, 1, 0, 0, 1), c(1, 1, 0, 1, 0))
data3 <- new("RtreemixData", Sample = bin.mat, Events = c("0", "1", "2",
"3"))
show(data3)
|
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