GEOlimma: differential expression analysis and feature selection using pre-existing microarray data

GEOlimma: differential expression analysis and feature selection using pre-existing microarray data

Background: Differential expression and feature selection analyses are essential steps for the development of accurate diagnostic/prognostic classifiers of complicated human diseases using transcriptomics data. These steps are particularly challenging due to the curse of dimensionality and the prese...

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Bibliographic Details
Main Authors: Daigle, B.J., Jr (Author), Lu, L. (Author), Townsend, K.A (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
Bayes theorem
Bayes Theorem
Biological pathways
biology
Cell proliferation
child
Child
Classification (of information)
Classification performance
Computational Biology
Curse of dimensionality
DE prior probabilities
Diagnosis
Differential expression
Differential gene expressions
Diseases
DNA microarray
Experimental conditions
Feature extraction
Feature selection
Feature selection methods
female
Female
Gene expression
gene expression profiling
Gene Expression Profiling
GEOlimma
human
Humans
male
Male
Oligonucleotide Array Sequence Analysis
Orbits
Pair-wise comparison
Probability
sample size
Sample Size
Signal transduction
Supervised classification
Supervised learning
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