ReadData: Function for preparing data object

In multiclassPairs: Build MultiClass Pair-Based Classifiers using TSPs or RF

Description

ReadData takes data such as matrix, labels, and platform information, and produce data object to be used in the down stream analysis, such as filtering genes.

Usage

ReadData(Data, Labels, Platform = NULL, verbose = TRUE)

Arguments

Data	a dataframe, matrix, or ExpressionSet with values to be used in the down stream analysis. Samples as columns and rows genes/features as rows. Matrix should has column names and row names. It is recommended to avoid "-" symbol for the feature/gene names.
Labels	a vector indicating the classes of the samples. Should be with the same length of the columns number in data. This can be a variable name stored in the ExpressionSet if ExpressionSet is used.
Platform	Optional, vector with the same length of labels indicating. This can be a variable name stored in the ExpressionSet if ExpressionSet is used.
verbose	a logical value indicating whether processing messages will be printed or not. Default is TRUE.

Value

data object multiclassPairs_object

Data	dataframe (gene as rows and samples as columns)
Labels	a vector containing classes information
Platform	a vector containing Platform information, or NULL if no input is used

Author(s)

Nour-al-dain Marzouka <nour-al-dain.marzouka at med.lu.se>

Examples

# example of loading data from matrix
Data <- matrix(runif(10000), nrow=100, ncol=100,
               dimnames = list(paste0("G",1:100), paste0("S",1:100)))

L <- sample(x = c("A","B","C"), size = 100, replace = TRUE)

P <- sample(x = c("P1","P2"), size = 100, replace = TRUE)


table(P,L)

object <- ReadData(Data = Data,
                   Labels = L,
                   Platform = P,
                   verbose = FALSE)
object


# Not to run
# example of loading data from ExpressionSet
# library(leukemiasEset, quietly = TRUE)
# data(leukemiasEset)

# split the data to training and testing
# n <- ncol(leukemiasEset)
# set.seed(1234)
# training_samples <- sample(1:n,size = n*0.6)

# train <- leukemiasEset[1:1000,training_samples]
# test  <- leukemiasEset[1:1000,-training_samples]

# create the data object
# when we use Expressionset we can use the name of the phenotypes variable
# ReadData will automatically extract the phenotype variable and use it as class labels
# the same can be used with the Platform/study labels
# in this example we are not using any platform labels, so leave it NULL
# object <- ReadData(Data = train,
#                   Labels = "LeukemiaType",
#                   Platform = NULL,
#                   verbose = FALSE)
# object

multiclassPairs documentation built on May 17, 2021, 1:06 a.m.