首页|Pretreating and normalizing metabolomics data for statistical analysis

Pretreating and normalizing metabolomics data for statistical analysis

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Metabolomics as a research field and a set of techniques is to study the entire small molecules in biological samples.Metabolomics is emerging as a powerful tool generally for pre-cision medicine.Particularly,integration of microbiome and metabolome has revealed the mechanism and functionality of microbiome in human health and disease.However,metabo-lomics data are very complicated.Preprocessing/pretreating and normalizing procedures on metabolomics data are usually required before statistical analysis.In this review article,we comprehensively review various methods that are used to preprocess and pretreat metabolo-mics data,including MS-based data and NMR-based data preprocessing,dealing with zero and/or missing values and detecting outliers,data normalization,data centering and scaling,data transformation.We discuss the advantages and limitations of each method.The choice for a suitable preprocessing method is determined by the biological hypothesis,the characteristics of the data set,and the selected statistical data analysis method.We then provide the perspective of their applications in the microbiome and metabolome research.

Data centering and scalingData normalizationData transformationMissing valuesMS-Based data preprocessingNMR Data preprocessingOutliersPreprocessing/pretreatment

Jun Sun、Yinglin Xia

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Division of Gastroenterology and Hepatology,Department of Medicine,Department of Microbiology/Immunology,UIC Cancer Center,University of Illinois Chicago,Jesse Brown VA Medical Center Chicago(537),Chicago,IL 60612,USA

Division of Gastroenterology and Hepatology,Department of Medicine,University of Illinois Chicago,Chicago,IL 60612,USA

Crohn's & Colitis Foundation Senior Research AwardNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Diabetes and Digestive and Kidney DiseasesUnited States Department of Defense Congressionally Directed Medical Research ProgramsVA Merit Award

902766R01DK105118-01RO1DK114126BC191198BX-19-00

2024

10.1016/j.gendis.2023.04.018

基因与疾病(英文)

基因与疾病(英文)

ISSN：
年,卷(期)：2024.11(3)
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