The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics
Open accessAbstract
Liquid chromatography coupled to high-resolution mass spectrometry platforms are increasingly employed to comprehensively measure metabolome changes in systems biology and complex diseases. Over the past decade, several powerful computational pipelines have been developed for spectral processing, annotation, and analysis. However, significant obstacles remain with regard to parameter settings, computational efficiencies, batch effects, and functional interpretations. Here, we introduce MetaboAnalystR 3.0, a significantly improved pipeline with three key new features: (1) efficient parameter optimization for peak picking; (2) automated batch effect correction; and (3) more accurate pathway activity prediction. Our benchmark studies showed that this workflow was 20~100× faster compared to other well-established workflows and produced more biologically meaningful results. In summary, MetaboAnalystR 3.0 offers an efficient pipeline to support high-throughput global metabolomics in the open-source R environment.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Adjusting batch effects in microarray expression data using empirical Bayes methods
Johnson, W. E., Li, C., & Rabinovic, A. (2007) · Biostatistics · doi:10.1093/biostatistics/kxj037 · Cited by 8,658
Smith, C. A., Want, E. J., O'Maille, G., Abagyan, R., & Siuzdak, G. (2006) · Analytical Chemistry · doi:10.1021/ac051437y · Cited by 5,262
Wang, M., Carver, J. J., Phelan, V. V., Sanchez, L. M., Garg, N., Peng, Y., Nguyen, D. D., Watrous, J., Kapono, C. A., Luzzatto-Knaan, T., et al. (2016) · Nature Biotechnology · doi:10.1038/nbt.3597 · Cited by 4,629
A cross-platform toolkit for mass spectrometry and proteomics
Chambers, M. C., Maclean, B., Burke, R., Amodei, D., Ruderman, D. L., Neumann, S., Gatto, L., Fischer, B., Pratt, B., Egertson, J., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2377 · Cited by 4,093
Pluskal, T., Castillo, S., Villar-Briones, A., & Orešič, M. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-395 · Cited by 3,845
The Human Serum Metabolome (HUSERMET) Consortium, Dunn, W. B., Broadhurst, D., Begley, P., Zelena, E., Francis-McIntyre, S., Anderson, N., Brown, M., Knowles, J. D., Halsall, A., et al. (2011) · Nature Protocols · doi:10.1038/nprot.2011.335 · Cited by 3,294
Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases
Lloyd-Price, J., Arze, C., Ananthakrishnan, A. N., Schirmer, M., Avila-Pacheco, J., Poon, T. W., Andrews, E., Ajami, N. J., Bonham, K. S., Brislawn, C. J., et al. (2019) · Nature · doi:10.1038/s41586-019-1237-9 · Cited by 3,143 · cited 18×
“Finally, the IBD data was first processed using the optimized parameters, followed by batch correction based on QC samples.”
BackgroundMethodInfluentialNormalization of RNA-seq data using factor analysis of control genes or samples
Risso, D., Ngai, J., Speed, T. P., & Dudoit, S. (2014) · Nature Biotechnology · doi:10.1038/nbt.2931 · Cited by 2,052
Multivariate analyses in microbial ecology
Ramette, A. (2007) · FEMS Microbiology Ecology · doi:10.1111/j.1574-6941.2007.00375.x · Cited by 1,928
Predicting Network Activity from High Throughput Metabolomics
Li, S., Park, Y., Duraisingham, S., Strobel, F. H., Khan, N., Soltow, Q. A., Jones, D. P., & Pulendran, B. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003123 · Cited by 936
Self-citation
Cited by
Pang, Z., Lu, Y., Zhou, G., Hui, F., Xu, L., Viau, C., Spigelman, A. F., MacDonald, P. E., Wishart, D. S., Li, S., et al. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae253 · Cited by 2,291
Self-citationPang, Z., Zhou, G., Ewald, J., Chang, L., Hacariz, O., Basu, N., & Xia, J. (2022) · Nature Protocols · doi:10.1038/s41596-022-00710-w · Cited by 1,444
Self-citationMetaboAnalystR 4.0: a unified LC-MS workflow for global metabolomics
Pang, Z., Xu, L., Viau, C., Lu, Y., Salavati, R., Basu, N., & Xia, J. (2024) · Nature Communications · doi:10.1038/s41467-024-48009-6 · Cited by 284
Self-citationFujihara, K. M., Zhang, B. Z., Jackson, T. D., Ogunkola, M. O., Nijagal, B., Milne, J. V., Sallman, D. A., Ang, C.-S., Nikolic, I., Kearney, C. J., et al. (2022) · Science Advances · doi:10.1126/sciadv.abm9427 · Cited by 102
“Statistical analysis was performed applying the web-based platform Metabo-Analyst applying no missing value imputation, normalization to median peak area, and no scaling or transformation ( 53 ).”
Goodrich, J. A., Walker, D. I., He, J., Lin, X., Baumert, B. O., Hu, X., Alderete, T. L., Chen, Z., Valvi, D., Fuentes, Z. C., et al. (2023) · Environmental Health Perspectives · doi:10.1289/ehp11372 · Cited by 96
Metadata
- Authors
- Pang, Z., Chong, J., Li, S., & Xia, J.
- Venue
- Metabolites
- Publisher
- MDPI AG
- Published
- 2020-05-07
- Volume
- 10
- Issue
- 5
- Pages
- 186
- ISSN
- 2218-1989 (ISSN-L)
- OpenAlex
- W3022658502
- Cited by
- 558
- References
- 42
- FWCI
- 24.96
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics. https://app.cochat.ai/papers/10.3390/metabo10050186
- The paper
- Pang, Z., Chong, J., Li, S., & Xia, J. (2020). MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics. Metabolites. https://doi.org/10.3390/metabo10050186
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
