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MiDA (version 0.1.2)

Microarray Data Analysis

Description

Set of functions designed to simplify transcriptome analysis and identification of marker molecules using microarrays data. The package includes a set of functions that allows performing full pipeline of analysis including data normalization, summarisation, binary classification, FDR (False Discovery Rate) multiple comparison and the definition of potential biological markers.

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Version

Install

install.packages('MiDA')

Monthly Downloads

36

Version

0.1.2

License

GPL-3

Maintainer

Elena Filatova

Last Published

April 18th, 2019

Functions in MiDA (0.1.2)

IMexpression

Infectious mononucleosis transcriptome
MiBiClassGBODT

Binary classification using gradient boosting over desicion trees
MiDataSample

Select matrix columns based on values of attendant vector
MiFracData

Subset an expression matrix based on probe's feature importance
MiInflCount

Mean microarray probes' feature importance from binary classification
MiIntDepthAjust

Ajust maximum depth parameter for fitting generalized boosted regression models
MiNTreesAjust

Ajust number of trees parameter for fitting generalized boosted regression models
MiNorm

Microarray data normalization
MiSelectSignif

Select biological markers with high fold change and classification importance
MiStatCount

FDR for microarray gene expression data
MiSummarize

Microarray data summarization
IMspecimen

Specimen features
MiShrinkAjust

Ajust learning rate parameter for fitting generalized boosted regression modelsfor fitting generalized boosted regression models
MiSpecimenSample

Select values from factor vector