Fahy E, Cotter D, Sud M, Subramaniam S. Lipid classification, structures and tools. Biochim Biophys Acta (BBA) - Mol Cell Biol Lipids. 2011;1811(11):637–47.

CAS  Google Scholar 

Wymann MP, Schneiter R. Lipid signalling in disease. Nat Rev Mol Cell Biol. 2008;9(2):162–76.

Article  CAS  PubMed  Google Scholar 

Carotti S, Aquilano K, Valentini F, Ruggiero S, Alletto F, Morini S, et al. An overview of deregulated lipid metabolism in nonalcoholic fatty liver disease with special focus on lysosomal acid lipase. Am J Physiol Gastrointest Liver Physiol. 2020;319(4):G469–80.

Article  CAS  PubMed  Google Scholar 

Bhargava S, De La Puente-Secades S, Schurgers L, Jankowski J. Lipids and lipoproteins in cardiovascular diseases: a classification. Trends Endocrinol Metab. 2022;33(6):409–23.

Article  CAS  PubMed  Google Scholar 

Eid S, Sas KM, Abcouwer SF, Feldman EL, Gardner TW, Pennathur S, et al. New insights into the mechanisms of diabetic complications: role of lipids and lipid metabolism. Diabetologia. 2019;62(9):1539–49.

Article  PubMed  PubMed Central  Google Scholar 

Perry RJ, Samuel VT, Petersen KF, Shulman GI. The role of hepatic lipids in hepatic insulin resistance and type 2 diabetes. Nature. 2014;510(7503):84–91.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Luo X, Cheng C, Tan Z, Li N, Tang M, Yang L, et al. Emerging roles of lipid metabolism in cancer metastasis. Mol Cancer. 2017;16(1).

Yadav RS, Tiwari NK. Lipid Integration in Neurodegeneration: An Overview of Alzheimer’s Disease. Mol Neurobiol. 2014;50(1):168–76.

Article  CAS  PubMed  Google Scholar 

Maradonna F, Carnevali O. Lipid Metabolism Alteration by Endocrine Disruptors in Animal Models: An Overview. Front Endocrinol (Lausanne). 2018;9:654.

Article  PubMed  PubMed Central  Google Scholar 

Fahy E, Sud M, Cotter D, Subramaniam S. LIPID MAPS online tools for lipid research. Nucleic Acids Res. 2007;35(Web Server issue):W606-12.

Article  PubMed  PubMed Central  Google Scholar 

Olshansky G, Giles C, Salim A, Meikle PJ. Challenges and opportunities for prevention and removal of unwanted variation in lipidomic studies. Prog Lipid Res. 2022;87:101177.

Article  CAS  PubMed  Google Scholar 

Xu T, Hu C, Xuan Q, Xu G. Recent advances in analytical strategies for mass spectrometry-based lipidomics. Anal Chim Acta. 2020;1137:156–69.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ni Z, Wölk M, Jukes G, Mendivelso Espinosa K, Ahrends R, Aimo L, et al. Guiding the choice of informatics software and tools for lipidomics research applications. Nat Methods. 2023;20(2):193–204.

Article  CAS  PubMed  Google Scholar 

Giles C, Takechi R, Lam V, Dhaliwal SS, Mamo JCL. Contemporary lipidomic analytics: opportunities and pitfalls. Prog Lipid Res. 2018;71:86–100.

Article  CAS  PubMed  Google Scholar 

Rubingh CM, Bijlsma S, Derks EPPA, Bobeldijk I, Verheij ER, Kochhar S, et al. Assessing the performance of statistical validation tools for megavariate metabolomics data. Metabolomics. 2006;2(2):53–61.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Floudas CA, Gounaris CE. A review of recent advances in global optimization. J Global Optim. 2009;45(1):3–38.

Article  MathSciNet  Google Scholar 

Wong G, Chan J, Kingwell BA, Leckie C, Meikle PJ. LICRE: unsupervised feature correlation reduction for lipidomics. Bioinformatics. 2014;30(19):2832–3.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Perez-Melo S, Kibria BMG. On Some Test Statistics for Testing the Regression Coefficients in Presence of Multicollinearity: A Simulation Study. Stats. 2020;3(1):40–55.

Article  Google Scholar 

Kanehisa M. The KEGG resource for deciphering the genome. Nucleic Acids Res. 2004;32(90001):277D – 80.

Article  Google Scholar 

Sun J, Xia Y. Pretreating and normalizing metabolomics data for statistical analysis. Genes Dis. 2023.

Saccenti E, Hoefsloot HCJ, Smilde AK, Westerhuis JA, Hendriks MMWB. Reflections on univariate and multivariate analysis of metabolomics data. Metabolomics. 2014;10(3):361–74.

Article  CAS  Google Scholar 

Vinaixa M, Samino S, Saez I, Duran J, Guinovart JJ, Yanes O. A Guideline to Univariate Statistical Analysis for LC/MS-Based Untargeted Metabolomics-Derived Data. Metabolites. 2012;2(4):775–95.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hines KM, Xu L. Lipidomic consequences of phospholipid synthesis defects in Escherichia coli revealed by HILIC-ion mobility-mass spectrometry. Chem Phys Lipids. 2019;219:15–22.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Bifarin OO, Sah S, Gaul DA, Moore SG, Chen R, Palaniappan M, et al. Machine Learning Reveals Lipidome Remodeling Dynamics in a Mouse Model of Ovarian Cancer. J Proteome Res. 2023;22(6):2092–108.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Vaz FM, Pras-Raves M, Bootsma AH, Van Kampen AHC. Principles and practice of lipidomics. J Inherit Metab Dis. 2015;38(1):41–52.

Article  CAS  PubMed  Google Scholar 

Peterson SJ, Foley S. Clinician’s Guide to Understanding Effect Size, Alpha Level, Power, and Sample Size. Nutr Clin Pract. 2021;36(3):598–605.

Article  PubMed  Google Scholar 

Fay MP, Proschan MA. Wilcoxon-Mann-Whitney or t-test? On assumptions for hypothesis tests and multiple interpretations of decision rules. Stat Surv. 2010;4(none):1–39.

Article  MathSciNet  PubMed  PubMed Central  Google Scholar 

Kujala M, Nevalainen J. A case study of normalization, missing data and variable selection methods in lipidomics. Stat Med. 2015;34(1):59–73.

Article  MathSciNet  CAS  PubMed  Google Scholar 

Ghasemi A, Zahediasl S. Normality Tests for Statistical Analysis: A Guide for Non-Statisticians. Int J Endocrinol Metab. 2012;10(2):486–9.

Article  PubMed  PubMed Central  Google Scholar 

Zhou Y, Zhu Y, Wong WK. Statistical tests for homogeneity of variance for clinical trials and recommendations. Contemp Clin Trials Commun. 2023;33:101119.

Article  PubMed  PubMed Central  Google Scholar 

Forstmeier W, Wagenmakers EJ, Parker TH. Detecting and avoiding likely false-positive findings – a practical guide. Biol Rev. 2017;92(4):1941–68.

Article  PubMed  Google Scholar 

Noble WS. How does multiple testing correction work? Nat Biotechnol. 2009;27(12):1135–7.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Simonsohn U, Nelson LD, Simmons JP. p-Curve and Effect Size: Correcting for Publication Bias Using Only Significant Results. Perspect Psychol Sci. 2014;9(6):666–81.

Article  PubMed  Google Scholar 

Alloghani M, Al-Jumeily D, Mustafina J, Hussain A, Aljaaf AJ. A Systematic Review on Supervised and Unsupervised Machine Learning Algorithms for Data Science. In: Berry M, Mohamed A, Yap B, editors. Supervised and Unsupervised Learning for Data Science. Springer, Cham; 2020. pp. 3–21.

Bro R, Smilde AK. Principal component analysis. Anal Methods. 2014;6(9):2812–31.

Article  CAS  Google Scholar 

Wu Z, Bagarolo GI, Thoroe-Boveleth S, Jankowski J. “Lipidomics”: Mass spectrometric and chemometric analyses of lipids. Adv Drug Deliv Rev. 2020;159:294–307.

Article  CAS  PubMed  Google Scholar 

Shen Q, Wang Y, Gong L, Guo R, Dong W, Cheung H-Y. Shotgun Lipidomics Strategy for Fast Analysis of Phospholipids in Fisheries Waste and Its Potential in Species Differentiation. J Agric Food Chem. 2012;60(37):9384–93.

Article  CAS  PubMed  Google Scholar 

Hancock SE, Ding E, Johansson Beves E, Mitchell T, Turner N. FACS-assisted single-cell lipidome analysis of phosphatidylcholines and sphingomyelins in cells of different lineages. J Lipid Res. 2023;64(3):100341.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Da Costa E, Domingues P, Melo T, Coelho E, Pereira R, Calado R, et al. Lipidomic Signatures Reveal Seasonal Shifts on the Relative Abundance of High-Valued Lipids from the Brown Algae Fucus vesiculosus. Mar Drugs. 2019;17(6):335.

Article  PubMed  PubMed Central  Google Scholar 

van der Maaten LH, Geoffrey. Viualizing data using t-SNE. J Mach Learn Res. 2008;2008(9):2579–605.

Google Scholar 

Wang Z, Zhang Y, Tian R, Luo Z, Zhang R, Li X, et al. Data-Driven Deciphering of Latent Lesions in Heterogeneous Tissue Using Function-Directed <i>t</i>-SNE of Mass Spectrometry Imaging Data. Anal Chem. 2022;94(40):13927–35.