weight.mbmr {BootMRMR} | R Documentation |
Computation of weights for informative gene selection using Modified Bootstrap MRMR technique
Description
Weights associated with genes in a dataset computed from the Modified Bootstrap MRMR technique will provide a reliable measure for informative gene selection.
Usage
weight.mbmr(x, y, m, s, plot)
Arguments
x |
x is a N by p dataframe of gene expression, where rows are genes and columns are as samples/subjects (gene names are taken as row names). |
y |
y is a p by 1 numeric vector with entries 1 and -1 representing sample labels, where 1 and -1 represents the sample label of subjects/ samples for stress and control condition respectively. |
m |
m is a scalar representing the size of the Modified Bootstrap Sample (i.e. Out of p samples/subjects, m samples/subjects are randomly drawn with replacement, which constitutes one Modified Bootstrap Sample). |
s |
s is a scalar representing the number of Modified Bootstrap samples (i.e. number of times each of the m samples/subjects will be resampled from p samples/subjects). |
plot |
plot is a character string must either take logical value TRUE/FALSE representing whether to plot the weights of genes in the dataset. |
Details
The function returns a vector of weights associated with each genes in the dataset using Modified Bootstrap MRMR technique.
Author(s)
Samarendra Das
References
Wang J, Chen L, Wang Y, Zhang J, Liang Y, Xu D (2013) A Computational systems biology study for understanding salt tolerance mechanism in Rice. PLoS one 8(6): e64929.
Examples
data(rice_salt)
x=as.data.frame(rice_salt[-1,])
y=as.numeric(rice_salt[1,])
m=36
s=80
weight.mbmr(x, y, m, s, plot=FALSE)