SMART 2.0 Statistical Metabolomics Analysis: An R Tool 2.0

Metabolomics has experienced significant growth and increased popularity due to technological advancements. We introduced an integrated tool for untargeted metabolomics analysis, SMART 1.0, that streamlined the entire analysis process, from initial data preprocessing to subsequent association analysis. With SMART 2.0, we enhanced SMART 1.0 by introducing new analytical modules in targeted metabolomics analysis, data normalization, quality control assessment, and advanced dimensionality reduction and classification methods. Additionally, SMART 2.0 offers integrative omics pathway analysis and postanalysis tasks such as peak identification and concentration calibration. We also explored the potential of using large language models for peak annotation and have found the results to be promising. This study employs narcotics data and breast cancer data as demonstrative examples to illustrate the new functionalities. The codes, a user guide, and example data can be downloaded at https://github.com/YuJenL/SMART.

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Publication Details

Journal
Analytical Chemistry
Published
2025-10-31
DOI
https://doi.org/10.1021/acs.analchem.5c03225
Citations
1
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
0.81
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article

SMART 2.0 Statistical Metabolomics Analysis: An R Tool 2.0

Chia‐Wei Chen, Yin-Chun Lin, Yu-Jen Liang, Chih-Ting Yang et al.
1 citations
Analytical Chemistry
Metabolomics and Mass Spectrometry Studies
0.81
article

SMART 2.0 Statistical Metabolomics Analysis: An R Tool 2.0

Chia‐Wei Chen, Yin-Chun Lin, Yu-Jen Liang, Chih-Ting Yang, Hsin‐Chou Yang, Yi‐Sheng Wang, Shu‐Yao Lin
article en
1 citations

Abstract

Metabolomics has experienced significant growth and increased popularity due to technological advancements. We introduced an integrated tool for untargeted metabolomics analysis, SMART 1.0, that streamlined the entire analysis process, from initial data preprocessing to subsequent association analysis. With SMART 2.0, we enhanced SMART 1.0 by introducing new analytical modules in targeted metabolomics analysis, data normalization, quality control assessment, and advanced dimensionality reduction and classification methods. Additionally, SMART 2.0 offers integrative omics pathway analysis and postanalysis tasks such as peak identification and concentration calibration. We also explored the potential of using large language models for peak annotation and have found the results to be promising. This study employs narcotics data and breast cancer data as demonstrative examples to illustrate the new functionalities. The codes, a user guide, and example data can be downloaded at https://github.com/YuJenL/SMART.

Analytical ChemistryVol. 97(46)
National Sun Yat-sen University (TW), National Yang Ming Chiao Tung University (TW), Genomics Research Center, Academia Sinica (TW), Biotechnology Research Center (IR), Institute of Biomedical Sciences, Academia Sinica (TW), Institute of Statistical Science, Academia Sinica (TW), Agricultural Biotechnology Research Center, Academia Sinica (TW), Genomics (United Kingdom) (GB), Academia Sinica (TW), National Cheng Kung University (TW)
Openalex Percentile: Top 22%
Metabolomics and Mass Spectrometry Studies
0.81
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SMART 2.0 Statistical Metabolomics Analysis: An R Tool 2.0 — Chia‐Wei Chen, Yin-Chun Lin, et al. · Analytical Chemistry (2025) | TGRS Research Map | TGRS