ArticleMethods in molecular biology (Clifton, N.J.)2022
Microarray Data Preprocessing: From Experimental Design to Differential Analysis.
Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Pipettes and Pipelines: The Weapons of Omics Sciences for a New Age of Clinical Studies.Current issues in molecular biology · 2026Review
- Integrating Microarray Analysis, Machine Learning, and Molecular Docking to Explore the Mechanism of Doxorubicin-induced Cardiotoxicity.Current medicinal chemistry · 2026Article
- Machine Learning in Stem Cell Research: From Biological Data to Clinical Translation.Computational and structural biotechnology journal · 2026Review
- Identification and correction of time-series transcriptomic anomalies.Nucleic acids research · 2025Article
- Ten quick tips for biomarker discovery and validation analyses using machine learning.PLoS computational biology · 2022Article
- Non-Coding RNAs in Tuberculosis Epidemiology: Platforms and Approaches for Investigating the Genome's Dark Matter.International journal of molecular sciences · 2022Review
Corrections and comments
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Authors and funding
7 authors.
Funding
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Abstract
DNA microarray data preprocessing is of utmost importance in the analytical path starting from the experimental design and leading to a reliable biological interpretation. In fact, when all relevant aspects regarding the experimental plan have been considered, the following steps from data quality check to differential analysis will lead to robust, trustworthy results. In this chapter, all the relevant aspects and considerations about microarray preprocessing will be discussed. Preprocessing steps are organized in an orderly manner, from experimental design to quality check and batch effect removal, including the most common visualization methods. Furthermore, we will discuss data representation and differential testing methods with a focus on the most common microarray technologies, such as gene expression and DNA methylation.
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Registered trials
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