Metabolomics FAQ

• • In Untargeted Metabolomics, What Is the Difference Between Performing PLS-DA Analysis and OPLS-DA Analysis

  PLS-DA (Partial Least Squares Discriminant Analysis) and OPLS-DA (Orthogonal Partial Least Squares Discriminant Analysis) are widely used multivariate statistical techniques in metabolomics for identifying metabolites that differ significantly between groups. While both methods are employed for classification and prediction tasks, they differ in their modeling approaches and interpretability.

• • How Can the OPLS-DA Permutation Test Plot Be Considered Not Overfitted

  When applying the OPLS-DA (Orthogonal Partial Least Squares Discriminant Analysis) model for permutation testing, it is crucial to evaluate the model's predictive accuracy, particularly the Q2 statistic, in relation to the distribution of Q2 values obtained from the permutations. Specifically: The Q2 statistic of the original model should exceed the distribution of Q2 values derived from the permuted datasets. This indicates that the model's performance with the original dataset is substantially better.....

• • How to Purify Polysaccharides Using a DEAE Column in Ion Exchange Chromatography?

  Polysaccharide purification methods vary based on the polysaccharide characteristics, desired purity, and experimental requirements. Common methods include gel filtration chromatography, ion exchange chromatography, affinity chromatography, thin-layer chromatography, and ultrafiltration. The DEAE (diethylaminoethyl) column, an anion exchange column, is commonly used in ion exchange chromatography to separate positively charged biological macromolecules from mixtures.   In ion exchange chromatography, ......

• • How to Identify Differentially Associated Genes for Differential Metabolites?

  After identifying differential metabolites, the following approaches can be used to search for genes associated with them:   Database and Literature Search Search for genes and biological pathways related to the metabolites by using their names or structures in literature databases (such as PubMed) and specialized metabolomics databases (such as HMDB, KEGG, MetaboAnalyst).   Bioinformatics Tools 1. MetaboAnalyst Input differential metabolite data to perform pathway enrichment analysis, identifying ass......

• • How to Construct an S-plot in OPLS-DA?

  S-plot is a widely used visualization tool in OPLS-DA or PLS-DA for identifying variables that contribute most to class separation. By integrating loadings and correlation coefficients, S-plot presents variables in a structured and interpretable manner. The following are the fundamental steps for constructing an S-plot analysis:   Data Preparation A dataset previously analyzed using OPLS-DA is required. This dataset should include measured values of relevant variables, such as metabolite concentration......

• • How Does LC/MS Perform MS1 and MS2 Detection?

  LC-MS is a technique that integrates liquid chromatography with mass spectrometry to achieve qualitative and quantitative analysis of complex samples. In LC-MS, MS1 and MS2 detections correspond to the first- and second-stage mass spectrometry analysis, respectively. Below is an overview of the process for performing MS1 and MS2 detection in LC-MS:   Liquid Chromatography Separation LC-MS begins with liquid chromatography separation, where components in the sample are separated using a stationary phas......

• • Which Sample Is Better for Metabolomics Analysis Serum or Plasma?

  Plasma and serum are widely used in metabolomics research, each offering distinct advantages and applications. The selection should be based on specific research objectives and experimental requirements. Below is an overview of their respective applications.   Plasma Applications 1. Investigation of Dynamic Metabolic Processes Plasma is obtained by centrifugation of anticoagulated blood and retains nearly all blood metabolites, including those involved in coagulation pathways. It is particularly suita......

• • How to Interpret the Loading Plot in OPLS-DA Analysis?

  Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) is a multivariate statistical method designed to extract meaningful patterns from high-dimensional datasets. It is widely applied in high-throughput analyses such as metabolomics and proteomics.   In OPLS-DA, the loading plot is a key visualization tool that facilitates the interpretation of variable contributions within the model. Each point in the loading plot represents a variable, with its position indicating its relative contributio......

• • Is the Insolubility of Polysaccharides in Water After Alcohol Precipitation a Normal Phenomenon?

  Alcohol precipitation involves increasing the concentration of alcohol (e.g., ethanol) to induce polysaccharide precipitation. This method is widely used to efficiently separate polysaccharides from complex biological mixtures.   The solubility of polysaccharides is influenced by their chemical structure and environmental factors, such as temperature, pH, and ionic strength. While some polysaccharides are highly soluble in water, others exhibit limited solubility. Alcohol precipitation can induce stru......

• • How Should Visualization Plots Be Interpreted in Metabolomics Data Analysis?

  Following bioinformatics analysis of metabolomics data, various types of visualization plots are typically generated, each providing distinct insights into the dataset. Proper interpretation of these plots enables a multi-dimensional understanding of metabolomic patterns:   Principal Component Analysis (PCA) Plot PCA is an unsupervised dimensionality reduction technique used to visualize the overall structure and distribution of the data. In a PCA plot, each point represents a sample, with closer poin......