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rMisbeta (version 1.0)

A Robust Missing Imputation Method for Gene Expression Data

Description

It was developed especially for gene expression and metabolomics data analysis when the datasets are corrupted by outliers and missing values. The beta-divergence method was used to impute the missing values and modify the outliers.

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Version

Install

install.packages('rMisbeta')

Monthly Downloads

33

Version

1.0

License

GPL (>= 2)

Maintainer

Shahjaman

Last Published

November 6th, 2020

Functions in rMisbeta (1.0)

RobMeanVar

This function estimates the robust mean and variance using beta-divergence method to reconstruct the data matrix.
OutMisDat

This function allows user's to add outliers and missing values in the original dataset
performance.eval

This function estimates the different performance indices like, TPR,TNR,FPR,FNR,AUC etc. for number of top genes
rMisbeta-package

A Robust Missing Imputation Method for Gene Expression and Metabolomics Data Analysis
remat

Reformulated data matrix after modification of outliers and missing imputation using beta divergence method
CalcMeanVar

This function estimates the robust mean and variance using beta-divergence method.
Sim2Group

This function Sim2Group() simulates the gene expression data for two groups using one-way ANOVA model