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mAPKL (version 1.4.0)

A Hybrid Feature Selection method for gene expression data

Description

We propose a hybrid FS method (mAP-KL), which combines multiple hypothesis testing and affinity propagation (AP)-clustering algorithm along with the Krzanowski & Lai cluster quality index, to select a small yet informative subset of genes.

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Version

Version

1.4.0

License

GPL (>= 2)

Maintainer

Argiris Sakellariou

Last Published

February 15th, 2017

Functions in mAPKL (1.4.0)

classification

Classify samples according to the SVM algorithm
Classify-class

Class "Classify"
probes2pathways

Extract pathways from "exemplars"
preprocess

Performs normalization and/or log2 transformation
mAPKL

The mAP-KL algorithm
mAPKL-package

A hybrid feature selection method for gene expression data
annotate

Genome annotation of the "exemplars".
Annot-class

Class "Annot"
NetAttr-class

Class "NetAttr"
mAPKLRes-class

Class "mAPKLRes"
netwAttr

Calculates network characteristics
metrics

Computes several clasification metrics
DataLD-class

Class "DataLD"
report

Produce an HTML report of the mAP-KL analysis
loadFiles

Imports gene expression data
sampling

Splits a dataset to a train and a test sets of a user defined percentage