Evaluating and minimizing batch effects in metabolomics

Adjusting batch effects in microarray expression data using empirical Bayes methods

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Power failure: why small sample size undermines the reliability of neuroscience

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Hierarchical Clustering Schemes

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Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry.

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Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors

Haghverdi, L., Lun, A. T. L., Morgan, M. D., & Marioni, J. C. (2018) · Nature Biotechnology · doi:10.1038/nbt.4091 · Cited by 2,416 · see citing works

Tackling the widespread and critical impact of batch effects in high-throughput data

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Emerging applications of metabolomics in drug discovery and precision medicine

Wishart, D. S. (2016) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2016.32 · Cited by 1,499 · see citing works

Multivariate Analysis in Metabolomics

Worley, B., & Powers, R. (2012) · Current Metabolomics · doi:10.2174/2213235x11301010092 · Cited by 1,361 · see citing works

Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools

Sud, M., Fahy, E., Cotter, D., Azam, K., Vadivelu, I., Burant, C., Edison, A. S., Fiehn, O., Higashi, R. M., Nair, K. S., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1042 · Cited by 1,008 · see citing works

Translational biomarker discovery in clinical metabolomics: an introductory tutorial

Xia, J., Broadhurst, D., Wilson, M., & Wishart, D. S. (2012) · Metabolomics · doi:10.1007/s11306-012-0482-9 · Cited by 958 · see citing works

Quantitative Serum Nuclear Magnetic Resonance Metabolomics in Cardiovascular Epidemiology and Genetics

Soininen, P., Kangas, A. J., Würtz, P., Suna, T., & Ala‐Korpela, M. (2015) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.114.000216 · Cited by 890 · see citing works

The future of NMR-based metabolomics

Markley, J. L., Brüschweiler, R., Edison, A. S., Eghbalnia, H. R., Powers, R., Raftery, D., & Wishart, D. S. (2016) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2016.08.001 · Cited by 885 · see citing works

Large-Scale Human Metabolomics Studies: A Strategy for Data (Pre-) Processing and Validation

Bijlsma, S., Bobeldijk, I., Verheij, E. R., Ramaker, R., Kochhar, S., Macdonald, I. A., van Ommen, B., & Smilde, A. K. (2005) · Analytical Chemistry · doi:10.1021/ac051495j · Cited by 869 · see citing works

Toward Merging Untargeted and Targeted Methods in Mass Spectrometry-Based Metabolomics and Lipidomics

Čajka, T., & Fiehn, O. (2015) · Analytical Chemistry · doi:10.1021/acs.analchem.5b04491 · Cited by 839 · see citing works

Modern analytical techniques in metabolomics analysis.

Zhang, A., Sun, H., Wang, P., Han, Y., & Wang, X.-J. (2012) · In Analysis · doi:10.1039/c1an15605e · Cited by 787 · see citing works

LC-MS-based metabolomics

Zhou, B., Xiao, J. F., Tuli, L., & Ressom, H. W. (2011) · Molecular BioSystems · doi:10.1039/c1mb05350g · Cited by 652 · see citing works

MetaboLights—an open-access general-purpose repository for metabolomics studies and associated meta-data

Haug, K., Salek, R. M., Conesa, P., Hastings, J., de Matos, P., Rijnbeek, M. L., Mahendraker, T., Williams, M., Neumann, S., Rocca‐Serra, P., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1004 · Cited by 647 · see citing works

Stable isotopically labeled internal standards in quantitative bioanalysis using liquid chromatography/mass spectrometry: necessity or not?

Stokvis, E., Rosing, H., & Beijnen, J. H. (2005) · Rapid Communications in Mass Spectrometry · doi:10.1002/rcm.1790 · Cited by 590 · see citing works

Collection, storage, preservation, and normalization of human urinary exosomes for biomarker discovery

Zhou, H., Yuen, P. S. T., Pisitkun, T., Gonzales, P. A., Yasuda, H., Dear, J. W., Gross, P., Knepper, M. A., & Star, R. A. (2006) · Kidney International · doi:10.1038/sj.ki.5000273 · Cited by 586 · see citing works

A pragmatic and readily implemented quality control strategy for HPLC-MS and GC-MS-based metabonomic analysis

Sangster, T., Major, H. J., Plumb, R. S., Wilson, A., & Wilson, I. D. (2006) · The Analyst · doi:10.1039/b604498k · Cited by 565 · see citing works

Analytical strategies for LC–MS-based targeted metabolomics

Lu, W., Bennett, B. D., & Rabinowitz, J. D. (2008) · Journal of Chromatography B · doi:10.1016/j.jchromb.2008.04.031 · Cited by 489 · see citing works

Adjustment of systematic microarray data biases

Benito, M., Parker, J., Du, Q., Wu, J., Xiang, D., Perou, C. M., & Marron, J. S. (2004) · Bioinformatics · doi:10.1093/bioinformatics/btg385 · Cited by 426 · see citing works

Quantitative analysis of the microbial metabolome by isotope dilution mass spectrometry using uniformly 13C-labeled cell extracts as internal standards

Wu, L., Mashego, M. R., van Dam, J. C., Proell, A. M., Vinke, J. L., Ras, C., van Winden, W. A., van Gulik, W. M., & Heijnen, J. J. (2004) · Analytical Biochemistry · doi:10.1016/j.ab.2004.09.001 · Cited by 423 · see citing works

Differential 12 C-/ 13 C-Isotope Dansylation Labeling and Fast Liquid Chromatography/Mass Spectrometry for Absolute and Relative Quantification of the Metabolome

Guo, K., & Li, L. (2009) · Analytical Chemistry · doi:10.1021/ac900166a · Cited by 398 · see citing works

Why Batch Effects Matter in Omics Data, and How to Avoid Them

Goh, W. W. B., Wang, W., & Wong, L. (2017) · Trends in biotechnology · doi:10.1016/j.tibtech.2017.02.012 · Cited by 397 · see citing works

Methods that remove batch effects while retaining group differences may lead to exaggerated confidence in downstream analyses

Nygaard, V., Rødland, E. A., & Hovig, E. J. (2015) · Biostatistics · doi:10.1093/biostatistics/kxv027 · Cited by 379 · see citing works

Non-targeted UHPLC-MS metabolomic data processing methods: a comparative investigation of normalisation, missing value imputation, transformation and scaling

Guida, R. D., Engel, J., Allwood, J. W., Weber, R. J. M., Jones, M. R., Sommer, U., Viant, M. R., & Dunn, W. B. (2016) · Metabolomics · doi:10.1007/s11306-016-1030-9 · Cited by 378 · see citing works

LC-MS-based methodology for global metabolite profiling in metabonomics/metabolomics

Theodoridis, G., Gika, H. G., & Wilson, I. D. (2008) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2008.01.008 · Cited by 371 · see citing works

Normalization method for metabolomics data using optimal selection of multiple internal standards

Sysi‐Aho, M., Katajamaa, M., Yetukuri, L., & Orešič, M. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-93 · Cited by 358 · see citing works

NOREVA: normalization and evaluation of MS-based metabolomics data

Li, B., Tang, J., Yang, Q., Li, S., Cui, X., Li, Y., Chen, Y., Xue, W., Li, X., & Zhu, F. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx449 · Cited by 357 · see citing works

Batch effects and the effective design of single-cell gene expression studies

Tung, P.-Y., Blischak, J. D., Hsiao, C. J., Knowles, D. A., Burnett, J. E., Pritchard, J. K., & Gilad, Y. (2017) · Scientific Reports · doi:10.1038/srep39921 · Cited by 356 · see citing works

A Strategy for Identifying Differences in Large Series of Metabolomic Samples Analyzed by GC/MS

Jonsson, P., Gullberg, J., Nordström, A., Kusano, M., Kowalczyk, M., Sjöstróm, M., & Möritz, T. (2004) · Analytical Chemistry · doi:10.1021/ac0352427 · Cited by 349 · see citing works

Controlled Attenuation Parameter (CAP): a noninvasive method for the detection of hepatic steatosis based on transient elastography

Myers, R. P., Pollett, A. F., Kirsch, R., Pomier–Layrargues, G., Beaton, M. D., Levstik, M. A., Duarte‐Rojo, A., Wong, D., Crotty, P., & Elkashab, M. (2012) · Liver International · doi:10.1111/j.1478-3231.2012.02781.x · Cited by 345 · see citing works

Systematic Error Removal Using Random Forest for Normalizing Large-Scale Untargeted Lipidomics Data

Fan, S., Kind, T., Čajka, T., Hazen, S. L., Tang, W. H. W., Kaddurah-Daouk, R. F., Irvin, M. R., Arnett, D. K., Barupal, D. K., & Fiehn, O. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.8b05592 · Cited by 340 · see citing works

A Guideline to Univariate Statistical Analysis for LC/MS-Based Untargeted Metabolomics-Derived Data

Vinaixa, M., Samino, S., Sáez, I., Durán, J., Guinovart, J. J., & Yanes, Ó. (2012) · Metabolites · doi:10.3390/metabo2040775 · Cited by 330 · see citing works

Systems biology, metabolic modelling and metabolomics in drug discovery and development

Kell, D. B. (2006) · Drug Discovery Today · doi:10.1016/j.drudis.2006.10.004 · Cited by 297 · see citing works

Sample normalization methods in quantitative metabolomics

Wu, Y., & Li, L. (2015) · Journal of Chromatography A · doi:10.1016/j.chroma.2015.12.007 · Cited by 282 · see citing works

Metabolite fingerprinting: detecting biological features by independent component analysis

Scholz, M., Gatzek, S., Sterling, A., Fiehn, O., & Selbig, J. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth270 · Cited by 278 · see citing works

UPLC-ESI-QTOF/MS and multivariate data analysis for blood plasma and serum metabolomics: Effect of experimental artefacts and anticoagulant

Barri, T., & Dragsted, L. O. (2013) · Analytica Chimica Acta · doi:10.1016/j.aca.2013.01.015 · Cited by 268 · see citing works

Optimized Preprocessing of Ultra-Performance Liquid Chromatography/Mass Spectrometry Urinary Metabolic Profiles for Improved Information Recovery

Veselkov, K., Karstens, L., Masson, P., Robinette, S. L., Want, E. J., Li, J. V., Barton, R. H., Boursier-Neyret, C., Walther, B., Ebbels, T. M. D., et al. (2011) · Analytical Chemistry · doi:10.1021/ac201065j · Cited by 267 · see citing works

High-throughput discovery metabolomics

Fuhrer, T., & Zamboni, N. (2014) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2014.08.006 · Cited by 267 · see citing works

Lessons from Controversy: Ovarian Cancer Screening and Serum Proteomics

Ransohoff, D. F. (2005) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/dji054 · Cited by 265 · see citing works

Standardizing GC–MS metabolomics

Kanani, H., Chrysanthopoulos, P. K., & Klapa, M. I. (2008) · Journal of Chromatography B · doi:10.1016/j.jchromb.2008.04.049 · Cited by 252 · see citing works

Molecular phenotyping of a UK population: defining the human serum metabolome

Dunn, W. B., Lin, W., Broadhurst, D., Begley, P., Brown, M., Zelena, E., Vaughan, A. A., Halsall, A., Harding, N., Knowles, J. D., et al. (2014) · Metabolomics · doi:10.1007/s11306-014-0707-1 · Cited by 251 · see citing works

Impact of Analytical Bias in Metabonomic Studies of Human Blood Serum and Plasma

Teahan, O., Gamble, S. C., Holmes, E. C., Waxman, J., Nicholson, J. K., Bevan, C. L., & Keun, H. C. (2006) · Analytical Chemistry · doi:10.1021/ac051972y · Cited by 242 · see citing works

Improved batch correction in untargeted MS-based metabolomics

Wehrens, R., Hageman, J. A., van Eeuwijk, F., Kooke, R., Flood, P. J., Wijnker, T. G., Keurentjes, J. J. B., Lommen, A., van Eekelen, H. D. L. M., Hall, R. D., et al. (2016) · Metabolomics · doi:10.1007/s11306-016-1015-8 · Cited by 242 · see citing works

Analytical and statistical approaches to metabolomics research

Issaq, H. J., Van, Q. N., Waybright, T. J., Muschik, G. M., & Veenstra, T. D. (2009) · Journal of Separation Science · doi:10.1002/jssc.200900152 · Cited by 227 · see citing works

Microbial metabolomics: toward a platform with full metabolome coverage

Werf, M. J. V. D., Overkamp, K. M., Muilwijk, B., Coulier, L., & Hankemeier, T. (2007) · Analytical Biochemistry · doi:10.1016/j.ab.2007.07.022 · Cited by 207 · see citing works

statTarget: A streamlined tool for signal drift correction and interpretations of quantitative mass spectrometry-based omics data

Luan, H., Ji, F., Chen, Y., & Cai, Z. (2018) · Analytica Chimica Acta · doi:10.1016/j.aca.2018.08.002 · Cited by 203 · see citing works

Urine stability for metabolomic studies: effects of preparation and storage

Saude, E. J., & Sykes, B. D. (2007) · Metabolomics · doi:10.1007/s11306-006-0042-2 · Cited by 199 · see citing works

Statistical Methods for Handling Unwanted Variation in Metabolomics Data

Livera, A. M. D., Sysi‐Aho, M., Jacob, L., Gagnon-Bartsch, J. A., Castillo, S., Simpson, J. A., & Speed, T. P. (2015) · Analytical Chemistry · doi:10.1021/ac502439y · Cited by 195 · see citing works

Normalizing and Integrating Metabolomics Data

Livera, A. M. D., Dias, D. A., Souza, D. P. D., Rupasinghe, T., Pyke, J. S., Tull, D., Roessner, U., McConville, M. J., & Speed, T. P. (2012) · Analytical Chemistry · doi:10.1021/ac302748b · Cited by 194 · see citing works

Meta-analysis of untargeted metabolomic data from multiple profiling experiments

Patti, G. J., Tautenhahn, R., & Siuzdak, G. E. (2012) · Nature Protocols · doi:10.1038/nprot.2011.454 · Cited by 190 · see citing works

NOREVA: enhanced normalization and evaluation of time-course and multi-class metabolomic data

Yang, Q., Wang, Y., Zhang, Y., Li, F., Xia, W., Zhou, Y., Qiu, Y., Li, H., & Zhu, F. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa258 · Cited by 186 · see citing works

Large-scale untargeted LC-MS metabolomics data correction using between-batch feature alignment and cluster-based within-batch signal intensity drift correction

Brunius, C. F., Shi, L. S., & Landberg, R. (2016) · Metabolomics · doi:10.1007/s11306-016-1124-4 · Cited by 184 · see citing works

Compensation for Systematic Cross-Contribution Improves Normalization of Mass Spectrometry Based Metabolomics Data

Redestig, H., Fukushima, A., Stenlund, H. C., Möritz, T., Arita, M., Saito, K., & Kusano, M. (2009) · Analytical Chemistry · doi:10.1021/ac901143w · Cited by 177 · see citing works

Controlling the quality of metabolomics data: new strategies to get the best out of the QC sample

Godzień, J., Alonso‐Herranz, V., Barbas, C., & Armitage, E. G. (2014) · Metabolomics · doi:10.1007/s11306-014-0712-4 · Cited by 174 · see citing works

Normalization and integration of large-scale metabolomics data using support vector regression

Shen, X., Gong, X., Cai, Y. A., Guo, Y., Tu, J., Li, H., Zhang, T., Wang, J., Xue, F., & Zhu, Z. (2016) · Metabolomics · doi:10.1007/s11306-016-1026-5 · Cited by 171 · see citing works

Metabolomics analysis I. Selection of biological samples and practical aspects preceding sample preparation

Álvarez-Sánchez, B., Priego‐Capote, F., & de Castro, M. D. L. (2009) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2009.12.003 · Cited by 169 · see citing works

Removal of batch effects using distribution-matching residual networks

Shaham, U., Stanton, K. P., Zhao, J., Li, H., Raddassi, K., Montgomery, R. R., & Kluger, Y. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx196 · Cited by 168 · see citing works

Characterising and correcting batch variation in an automated direct infusion mass spectrometry (DIMS) metabolomics workflow

Kirwan, J., Broadhurst, D., Davidson, R., & Viant, M. R. (2013) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-013-6856-7 · Cited by 158 · see citing works

Metabolomics Data Normalization with EigenMS

Karpievitch, Y. V., Nikolic, S. B., Wilson, R., Sharman, J. E., & Edwards, L. M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0116221 · Cited by 144 · see citing works

A new statistic for identifying batch effects in high-throughput genomic data that uses guided principal component analysis

Reese, S. E., Archer, K. J., Therneau, T. M., Atkinson, E. J., Vachon, C. M., de Andrade, M., Kocher, J., & Eckel‐Passow, J. E. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt480 · Cited by 143 · see citing works

Intra-batch effect correction in liquid chromatography-mass spectrometry using quality control samples and support vector regression (QC-SVRC)

Kuligowski, J., Illana, Á. S., Sanjuan-Herráez, J. D., Vento, M., & Quintás‐Cardama, A. (2015) · The Analyst · doi:10.1039/c5an01638j · Cited by 122 · see citing works

Normalization of peak intensities in bottom-up MS-based proteomics using singular value decomposition

Karpievitch, Y. V., Taverner, T., Adkins, J., Callister, S., Anderson, G., Smith, R. D., & Dabney, A. R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp426 · Cited by 119 · see citing works

Evaluation of Normalization Methods to Pave the Way Towards Large-Scale LC-MS-Based Metabolomics Profiling Experiments

Ejigu, B. A., Valkenborg, D., Baggerman, G., Vanaerschot, M., Witters, E., Dujardin, J., Burzykowski, T., & Berg, M. (2013) · OMICS A Journal of Integrative Biology · doi:10.1089/omi.2013.0010 · Cited by 113 · see citing works

Experimental and Analytical Variation in Human Urine in 1H NMR Spectroscopy-Based Metabolic Phenotyping Studies

Maher, A. D., Zirah, S., Holmes, E. C., & Nicholson, J. K. (2007) · Analytical Chemistry · doi:10.1021/ac070212f · Cited by 112 · see citing works

Best-Matched Internal Standard Normalization in Liquid Chromatography–Mass Spectrometry Metabolomics Applied to Environmental Samples

Boysen, A. K., Heal, K. R., Carlson, L. T., & Ingalls, A. E. (2017) · Analytical Chemistry · doi:10.1021/acs.analchem.7b04400 · Cited by 109 · see citing works

Meta‐analysis of clinical metabolic profiling studies in cancer: challenges and opportunities

Goveia, J., Pircher, A., Conradi, L., Kalucka, J. M., Lagani, V., Dewerchin, M. A., Eelen, G., DeBerardinis, R. J., Wilson, I. D., & Carmeliet, P. (2016) · EMBO Molecular Medicine · doi:10.15252/emmm.201606798 · Cited by 106 · see citing works

Determination of Total Concentration of Chemically Labeled Metabolites as a Means of Metabolome Sample Normalization and Sample Loading Optimization in Mass Spectrometry-Based Metabolomics

Wu, Y., & Li, L. (2012) · Analytical Chemistry · doi:10.1021/ac3025625 · Cited by 105 · see citing works

A novel approach to transforming a non-targeted metabolic profiling method to a pseudo-targeted method using the retention time locking gas chromatography/mass spectrometry-selected ions monitoring

Li, Y., Ruan, Q., Li, Y., Ye, G., Lu, X., Lin, X., & Xu, G. (2012) · Journal of Chromatography A · doi:10.1016/j.chroma.2012.01.076 · Cited by 103 · see citing works

Batch Normalizer: A Fast Total Abundance Regression Calibration Method to Simultaneously Adjust Batch and Injection Order Effects in Liquid Chromatography/Time-of-Flight Mass Spectrometry-Based Metabolomics Data and Comparison with Current Calibration Methods

Wang, S., Kuo, C., & Tseng, Y. J. (2012) · Analytical Chemistry · doi:10.1021/ac302877x · Cited by 101 · see citing works

Metabolomics studies in brain tissue: A review

González-Riaño, C., Garcı́a, A., & Barbas, C. (2016) · Journal of Pharmaceutical and Biomedical Analysis · doi:10.1016/j.jpba.2016.07.008 · Cited by 101 · see citing works

Targeted Metabolomics of Dried Blood Spot Extracts

Zukunft, S., Sorgenfrei, M., Prehn, C. P., Möller, G., & Adamski, J. (2013) · Chromatographia · doi:10.1007/s10337-013-2429-3 · Cited by 100 · see citing works

Development of a Universal Metabolome-Standard Method for Long-Term LC–MS Metabolome Profiling and Its Application for Bladder Cancer Urine-Metabolite-Biomarker Discovery

Peng, J., Chen, Y., Chen, C., & Li, L. (2014) · Analytical Chemistry · doi:10.1021/ac5011684 · Cited by 99 · see citing works

Evaluation of intensity drift correction strategies using MetaboDrift, a normalization tool for multi-batch metabolomics data

Thonusin, C., IglayReger, H. B., Soni, T., Rothberg, A. E., Burant, C., & Evans, C. R. (2017) · Journal of Chromatography A · doi:10.1016/j.chroma.2017.09.023 · Cited by 98 · see citing works

Toward a Standardized Strategy of Clinical Metabolomics for the Advancement of Precision Medicine

Long, N. P., Nghi, T. D., Kang, Y. P., Anh, N. H., Kim, H. M., Park, S. K., & Kwon, S. W. (2020) · Metabolites · doi:10.3390/metabo10020051 · Cited by 93 · see citing works

Extraction parameters for metabolomics from cultured cells

Ser, Z., Liu, X., Tang, N. N., & Locasale, J. W. (2015) · Analytical Biochemistry · doi:10.1016/j.ab.2015.01.003 · Cited by 91 · see citing works

Quantification and statistical significance analysis of group separation in NMR-based metabonomics studies

Goodpaster, A. M., & Kennedy, M. (2011) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2011.08.009 · Cited by 85 · see citing works

Effects of processing and storage conditions on charged metabolomic profiles in blood

Hirayama, A., Sugimoto, M., Suzuki, A., Hatakeyama, Y., Enomoto, A., Harada, S., Soga, T., Tomita, M., & Takebayashi, T. (2015) · Electrophoresis · doi:10.1002/elps.201400600 · Cited by 78 · see citing works

Streamlined pentafluorophenylpropyl column liquid chromatography–tandem quadrupole mass spectrometry and global 13C-labeled internal standards improve performance for quantitative metabolomics in bacteria

Yang, S., Sadı́lek, M., & Lidstrom, M. E. (2010) · Journal of Chromatography A · doi:10.1016/j.chroma.2010.09.055 · Cited by 76 · see citing works

NormAE: Deep Adversarial Learning Model to Remove Batch Effects in Liquid Chromatography Mass Spectrometry-Based Metabolomics Data

Rong, Z., Tan, Q., Cao, L., Zhang, L., Deng, K., Huang, Y., Zhu, Z., Li, Z., & Li, K. (2020) · Analytical Chemistry · doi:10.1021/acs.analchem.9b05460 · Cited by 72 · see citing works

Comprehensive and simultaneous coverage of lipid and polar metabolites for endogenous cellular metabolomics using HILIC-TOF-MS

Fan, F., Bowdish, D. M. E., & McCarry, B. E. (2014) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-014-7797-5 · Cited by 71 · see citing works

Evaluation of Peak Picking Quality in LC−MS Metabolomics Data

Brodsky, L., Moussaieff, A., Shahaf, N., Aharoni, A., & Rogachev, I. (2010) · Analytical Chemistry · doi:10.1021/ac101216e · Cited by 69 · see citing works

Batch effects and the effective design of single-cell gene expression studiesPreprint

Tung, P., Blischak, J., Hsiao, C. J., et al. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/062919 · Cited by 69 · see citing works

Intensity drift removal in LC/MS metabolomics by common variance compensation

Fernández-Albert, F., Llorach, R., Garcia‐Aloy, M., Ziyatdinov, A., Andrés‐Lacueva, C., & Perera-Lluna, A. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu423 · Cited by 68 · see citing works

Evaluation of batch effect elimination using quality control replicates in LC-MS metabolite profiling

Illana, Á. S., Piñeiro-Ramos, J. D., Sanjuan-Herráez, J. D., Vento, M., Quintás‐Cardama, A., & Kuligowski, J. (2018) · Analytica Chimica Acta · doi:10.1016/j.aca.2018.02.053 · Cited by 65 · see citing works

High-resolution serum proteomic patterns for ovarian cancer detection

Baggerly, K., Edmonson, S. R., Morris, J. S., & Coombes, K. R. (2004) · Endocrine Related Cancer · doi:10.1677/erc.1.00868 · Cited by 64 · see citing works

WaveICA: A novel algorithm to remove batch effects for large-scale untargeted metabolomics data based on wavelet analysis

Deng, K., Zhang, F., Tan, Q., Huang, Y., Song, W., Rong, Z., Zhu, Z., Li, K., & Li, Z. (2019) · Analytica Chimica Acta · doi:10.1016/j.aca.2019.02.010 · Cited by 63 · see citing works

Instrumental and experimental effects in LC–MS-based metabolomics

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Metabolomic Alterations in Patients with Obesity and the Impact of Metabolic Bariatric Surgery: Insights for Future Research

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mzQuality: A tool for quality monitoring and reporting of targeted mass spectrometry measurementsPreprint

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Association between Higher Intake of Flavonols and Lignans and Better Mood: Evidence from Dietary and Biomarker Evaluation in Healthy Individuals

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Exploring Sample Storage Conditions for the Mass Spectrometric Analysis of Extracted Lipids from Latent Fingerprints

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A mathematical method for calibrating the signal drift in liquid chromatography - mass spectrometry analysis

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Decoding immune cell interactions during cardiac allograft vasculopathy: insights derived from bioinformatic strategies

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Integrating Advanced Metabolomics and Machine Learning for Anti-Doping in Human Athletes

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Contaminants of Concern and Spatiotemporal Metabolomic Changes in Quagga Mussels (Dreissena bugensis rostriformis) from the Milwaukee Estuary (Wisconsin, USA)

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High-Throughput Metabolomics using 96-plex Isotope Tagging

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Norm ISWSVR Enhanced Data Repeatability and Accuracy in Large-Scale Targeted Quantification Metabolomics

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Classification of Apples (Malus × domestica borkh.) According to Geographical Origin, Variety and Production Method Using Liquid Chromatography Mass Spectrometry and Random Forest

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Modelling single-stress omics integration with HIVE enables the identification of responding signatures to multifactorial stress combinations in plantsPreprint

Calia, G., Marguerit, S., Mota, A. P. Z., Vidal, M., Schuler, H., Brasileiro, A. C. M., Guimarães, P. M., & Bottini, S. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.03.04.583290 · Cited by 2 · see citing works

Extracellular vesicle proteomic expression is influenced by mining tenure in former uranium miners

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AI-Driven Quantitative Metabolomics for Early and Precise HIE Diagnosis: Challenges and Solutions

Panigrahi, A., Das, N. R., Yadav, N., Panda, S., Sethy, A. S., Panda, S. K., Mohakud, N. K., & Tiwari, V. (2025) · ACS Omega · doi:10.1021/acsomega.5c03256 · Cited by 1 · see citing works

Untargeted Metabolomics in Fermented Food Systems

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Preparation and Curation of Omics Data for Genome-Wide Association Studies

Zhu, F., Fernie, A. R., & Scossa, F. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-2237-7_8 · Cited by 1 · see citing works

Effects of Amphetamine-Type Stimulants on the Metabolome

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Long-Term Metabolomics Reference MaterialPreprint

Gouveia, G. J., Shaver, A. O., Garcia, B. M., Morse, A. M., Andersen, E. C., Edison, A. S., & McIntyre, L. M. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.24.436834 · Cited by 1 · see citing works

Batch Effect Correction in a Functional Colorectal Cancer Organoid Clinical Correlation StudyPreprint

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Identification of Key Immune-Related Genes, Molecular Pathways and Immune Infiltration as Diagnostic and Therapeutic Candidate Targets for RA: an integrated bioinformatics-based analysisPreprint

Fang, S., Fang, X., Xu, X. P., Zhong, L., Wang, A., Gao, W., & Yin, Z. (2021) · Research Square · doi:10.21203/rs.3.rs-296982/v1

Effects of Amphetamine-Type Stimulants on the Metabolome

Steuer, A. E. (2022) · Springer eBooks · doi:10.1007/978-3-030-67928-6_122-1

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

Li, D., Liang, J., Zhang, Y., & Zhang, G. (2022) · Journal of Visualized Experiments · doi:10.3791/63625

Targeted Metabolomics on Rare Primary Cells

Glaser, K. M., Egg, M., Hobitz, S., Mitterer, M., Schain-Zota, D., Schönberger, K., Schuldes, K., Cabezas‐Wallscheid, N., Lämmermann, T., Rambold, A. S., et al. (2024) · Journal of Visualized Experiments · doi:10.3791/65690

EigenRF: an improved metabolomics normalization method with scores for reproducibility evaluation on importance rankings of differential metabolites

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Alterations in plasma metabolome and correlation with urinary metabolome in cardiac surgery-associated acute kidney injury using ultra high-performance liquid chromatography-high resolution mass spectrometry

Bai, Y., JIANG, Y., Zhenmi, L. I. U., Liu, T., Liang, S., Feng, W. A. N. G., Zhang, L., Xin, L. I. U., Hu, L., & Chen, C. (2025) · Chinese Journal of Analytical Chemistry · doi:10.1016/j.cjac.2025.100587

Matrix effects influence biochemical signatures and metabolite quantification in dried blood spotsPreprint

Cremer, J.-C., Jurić, V., Koch, J. M., Scholl‐Bürgi, S., Karall, D., Zschocke, J., & Keller, M. A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.22.666056

Total Survey Error in Biomeasure Data CollectionPreprint

Cernat, A., Edwards, B., Mitchell, C. M., & Sakshaug, J. W. (2025) · Research Square · doi:10.21203/rs.3.rs-7711723/v1

HGAlign: Biologically preserving batch correction and classification for metabolomics via heterogeneous graph alignment

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Additional file 1 of Multi-omics profiles of the intestinal microbiome in irritable bowel syndrome and its bowel habit subtypes

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Additional file 2 of Correcting batch effects in large-scale multiomics studies using a reference-material-based ratio method

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Additional file 1 of Correcting batch effects in large-scale multiomics studies using a reference-material-based ratio method

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Targeted and Untargeted Metabolomics for Algal Characterization and Application

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Longitudinal, Intra-Individual Stability of Untargeted Plasma and Cerebrospinal Fluid Metabolites

Rocha, B. L., Jonaitis, E. M., Hamwi, A., & Engelman, C. D. (2025) · Metabolites · doi:10.3390/metabo16010035

Targeted and Untargeted Metabolomics for Algal Characterization and Application

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Decoding the Complexity of COPD, Multi – Omics approaches to Diagnosis and Treatment

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Advances in AI-enabled digital integration for geographical origin authenticity of staple crops: Omics-based molecular and elemental strategies

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Electrochemical viscosity correction for robust salivary ionomics via redox probe voltammetry.

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DCVBin: a novel binning method for single-sample metagenomes based on DNA language model and variational autoencoder

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Internal Circadian Misalignment of the Human Metabolome Links Night Shiftwork to Metabolic Impairment

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Metabolic signatures of triple-negative breast cancer

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Hierarchical mixed-effects model for batch effect correction in primary-tissue single-cell metabolomics by mass spectrometry

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MPR-MOPSO-ASFS: A Stable Multi-Objective Feature Selection Algorithm for Metabolomics

Ye, Q., Deng, Z., Xie, X., Huang, Q., & Luo, J. (2026) · Metabolites · doi:10.3390/metabo16080581

Detecting and Quantifying Variability in Mass Spectrometry-Based Metabolomics Datasets

Chua, A. E., & Desaire, H. (2026) · Biomolecules · doi:10.3390/biom16101399

Improved batch correction in untargeted MS-based metabolomics

Wehrens, R., Hageman, J. A., van Eeuwijk, F., Kooke, R., Flood, P. J., Wijnker, T. G., Keurentjes, J. J. B., Lommen, A., van Eekelen, H. D. L. M., Hall, R. D., et al. (2016) · Metabolomics · doi:10.1007/s11306-016-1015-8 · Cited by 242 · see citing works

Addressing the batch effect issue for LC/MS metabolomics data in data preprocessing

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Simulation-based comprehensive study of batch effects in metabolomics studiesPreprint

Yu, M., Roszkowska, A., & Pawliszyn, J. B. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2019.12.16.878637 · Cited by 1 · see citing works

Concordance-Based Batch Effect Correction for Large-Scale Metabolomics

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RRmix: A method for simultaneous batch effect correction and analysis of metabolomics data in the absence of internal standards

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