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BootMRMR (version 0.1)

Bootstrap-MRMR Technique for Informative Gene Selection

Description

Selection of informative features like genes, transcripts, RNA seq, etc. using Bootstrap Maximum Relevance and Minimum Redundancy technique from a given high dimensional genomic dataset. Informative gene selection involves identification of relevant genes and removal of redundant genes as much as possible from a large gene space. Main applications in high-dimensional expression data analysis (e.g. microarray data, NGS expression data and other genomics and proteomics applications).

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Version

Install

install.packages('BootMRMR')

Monthly Downloads

187

Version

0.1

License

GPL (>= 2)

Maintainer

Samarendra Das

Last Published

September 12th, 2016

Functions in BootMRMR (0.1)

mbmr.weight.cutoff

Identification of informative geneset based on weights obtained from Modified Bootstrap-MRMR technique
geneslect.f

Informative gene set selection using F-score
rice_salt

A gene expression dataset of rice under salinity stress
pval.mbmr

Computation of statistical significance values for genes using Modified Bootstrap MRMR technique for a particular trait/condition
bootmr.weight

Computation of weights for informative genes/ geneset selection using Bootstrap-MRMR technique
mrmr.cutoff

Informative geneset selection using MRMR weights
bmrmr.pval.cutoff

Selection of informative geneset based on statistical significance value using Bootstrap-MRMR technique
mbmr.pval.cutoff

Selection of informative geneset based on statistical significance value using Modified Bootstrap MRMR technique
pval.bmrmr

Compuation of statistical significance values for genes using Bootstrap-MRMR technique
weight.mbmr

Computation of weights for informative gene selection using Modified Bootstrap MRMR technique
topsis.meth

Selection of optimal gene selection method(s)/method(s) through multi-criteria decision analysis
bmrmr.weight.cutoff

Selection of informative geneset using gene weights obtained from the Bootstrap-MRMR technique
Weights.mrmr

Computation of MRMR weights for gene selection