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propOverlap  

Feature (gene) selection based on the Proportional Overlapping Scores
View on CRAN: Click here


Download and install propOverlap package within the R console
Install from CRAN:
install.packages("propOverlap")

Install from Github:
library("remotes")
install_github("cran/propOverlap")

Install by package version:
library("remotes")
install_version("propOverlap", "1.0")



Attach the package and use:
library("propOverlap")
Maintained by
Osama Mahmoud
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-09-15
Latest Update: 2014-09-15
Description:
A package for selecting the most relevant features (genes) in the high-dimensional binary classification problems. The discriminative features are identified using analyzing the overlap between the expression values across both classes. The package includes functions for measuring the proportional overlapping score for each gene avoiding the outliers effect. The used measure for the overlap is the one defined in the "Proportional Overlapping Score (POS)" technique for feature selection. A gene mask which represents a gene's classification power can also be produced for each gene (feature). The set size of the selected genes might be set by the user. The minimum set of genes that correctly classify the maximum number of the given tissue samples (observations) can be also produced.
How to cite:
Osama Mahmoud (2014). propOverlap: Feature (gene) selection based on the Proportional Overlapping Scores. R package version 1.0, https://cran.r-project.org/web/packages/propOverlap. Accessed 21 Nov. 2024.
Previous versions and publish date:
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Complete documentation for propOverlap
Functions, R codes and Examples using the propOverlap R package
Some associated functions: CoreIntervals . GMask . POS . RDC . Sel.Features . leukaemia . lung . propOverlap-internals . propOverlap-package . 
Some associated R codes: CoreIntervals.R . GMask.R . Min.Set.R . POS.R . RDC.R . Sel.Features.R . block.R .  Full propOverlap package functions and examples
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