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A comparison of RNA-Seq data preprocessing pipelines for transcriptomic predictions across independent studies

Abstract Background RNA sequencing combined with machine learning techniques has provided a modern approach to the molecular classification of cancer. Class predictors, reflecting the disease class, can be constructed for known tissue types using the gene expression measurements extracted from cance...

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Principais autores: Richard Van, Daniel Alvarez, Travis Mize, Sravani Gannavarapu, Lohitha Chintham Reddy, Fatma Nasoz, Mira V. Han
Format: Artigo
Sprog:Inglês
Udgivet: BMC 2024-05-01
Serier:BMC Bioinformatics
Fag:
RNA-Seq
Classification
Cancer
Batch effect correction
Normalization
Data scaling
Online adgang:https://doi.org/10.1186/s12859-024-05801-x
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