Literature DB >> 28502011

Metabolomic Bioinformatic Analysis.

Allyson L Dailey1.   

Abstract

Metabolomics allows for the investigation of the small molecules found within living systems. Based on the design of the experiments, it is not uncommon for these analyses to include matrices of thousands of variables. In order to handle such large datasets, many have turned to multivariate statistical analyses to analyze and understand their data. Herein, we present protocols for using R to analyze metabolomic data using some of the more common multivariate statistical techniques.

Keywords:  Correlation network; Data analysis; Dendrograms; Metabolomics; PCA; Pheatmap; Qgraph; R programming language; Rgl

Mesh:

Year:  2017        PMID: 28502011     DOI: 10.1007/978-1-4939-6990-6_22

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  4 in total

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3.  Colon cancer-specific diagnostic and prognostic biomarkers based on genome-wide abnormal DNA methylation.

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  4 in total

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