Feature-specific quantile normalization and feature-specific mean–variance normalization deliver robust bi-directional classification and feature selection performance between microarray and RNAseq data

Abstract Background Cross-platform normalization seeks to minimize technological bias between microarray and RNAseq whole-transcriptome data. Incorporating multiple gene expression platforms permits external validation of experimental findings, and augments training sets for machine learning models....

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Auteurs principaux:	Daniel Skubleny, Sunita Ghosh, Jennifer Spratlin, Daniel E. Schiller, Gina R. Rayat
Format:	Artigo
Langue:	Inglês
Publié:	BMC 2024-03-01
Collection:	BMC Bioinformatics
Sujets:	Cross-platform normalization Molecular classification Microarray RNAseq Feature selection Quantile normalization
Accès en ligne:	https://doi.org/10.1186/s12859-024-05759-w
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