Bioinformatics Analysis FAQ

• • How to Perform PLS-DA and OPLS-DA Analysis and Visualization in R?

  Performing PLS-DA (Partial Least Squares Discriminant Analysis) and OPLS-DA (Orthogonal Partial Least Squares Discriminant Analysis) in R, along with generating relevant visualizations, requires the use of specific R packages. The general workflow consists of the following steps:   1. Preparation Before conducting the analysis, users must install appropriate R packages that provide the necessary functions for PLS-DA and OPLS-DA. Commonly used packages include mixOmics, ropls, and pls.   2. Data Prepro......

• • How to Identify Relevant Pathways from GO and KEGG Enrichment Analysis? What Approach and Databases Are Recommended?

  The identification of pathways relevant to research objectives using GO and KEGG enrichment analysis can be achieved through the following approach:   Clarifying Research Background and Objectives Before conducting enrichment analysis, it is crucial to define the research objectives and hypotheses. Understanding the biological processes, diseases, or conditions of interest helps pinpoint the most relevant pathways.   Performing GO and KEGG Enrichment Analysis Utilize appropriate bioinformatics too......

• • What to Do if Many Data Points Are Outliers in PLS-DA Fitting? Is the Data Still Valid?

  When performing PLS-DA fitting, the appearance of many outliers may indicate issues such as overfitting or other model-related problems. Below are several solutions and suggestions to address this issue:   Verify Data Quality The first step is to check the data's quality and accuracy. Inspect the data for outliers, missing values, or other potential errors. If any data quality issues are found, reprocessing or cleaning the data may be necessary to ensure reliable results.   Feature Selection If the da......

• • After KEGG Identifies Pathways, Where to See Each Pathway's Function?

  After using the KEGG (Kyoto Encyclopedia of Genes and Genomes) database to obtain signaling pathways, you can directly view detailed information and functions for each pathway within the KEGG database. KEGG provides extensive pathway maps and related details that help in understanding the biological functions and mechanisms of the pathways.   Visit the KEGG Website Navigate to the official KEGG PATHWAY Database on the KEGG website.   Search for a Specific Pathway Enter the name or KEGG identifier of t......

• • How to Handle log2foldchange with Zero FPKM in KEGG Enrichment Analysis?

  When performing KEGG enrichment analysis, if the FPKM value in the control or treatment group is 0, the log2foldchange can be handled by the following methods:   Add a Small Constant Value Before calculating log2foldchange, add a small constant (e.g., 0.1 or 0.01) to all FPKM values. This avoids log2(0) while preserving the relative nature of the data. This method is suitable when many genes have low expression.   Use Estimated Values Replace a 0 FPKM value with an estimated value, such as the lower d......

• • How to Process Large-Scale Proteomics (Qualitative and Quantitative Detection) Data?

  When processing large-scale proteomics (qualitative and quantitative detection) data, you can follow these steps:   Data Preprocessing 1. Data Cleaning Remove noise, outliers, and missing values to ensure data quality and integrity.   2. Data Normalization Normalize the data to eliminate technical differences between samples.   3. Data Transformation Transform the data, such as logarithmic transformation or standardization, to meet statistical analysis requirements.   Protein Identification and Quanti......

• • Does PCA with Only One Factor Represent a Single Dimension?

  Yes, if principal component analysis (PCA) extracts only one principal component (or "factor"), it can be considered the main dimension in the data that captures the greatest variance. This means that this single principal component summarizes the primary pattern or trend of variation in the data.   Extracting a single principal component is meaningful in certain cases, especially when that component explains most of the variance in the data. However, the decision to extract only one principal compone......

• • How to Use the GO Database to Find a Gene's Function, Cellular Localization, and Involved Biological Processes?

  First, visit the official Gene Ontology (GO) database website and enter the gene name or ID in the search box. The GO database supports common names, aliases, or specific database IDs. After submitting the search, the database will display detailed information about the gene, including an overview, functional description, cellular location, and involved biological processes.   Gene function usually describes the biochemical activity of the protein or RNA encoded by the gene, such as enzymatic activity......

• • How to Use the KEGG Database to Retrieve Metabolic Pathways of a Specific Microorganism

  To retrieve metabolic pathways for a specific microorganism using the KEGG database, follow these steps:   1. Navigate to the KEGG database website (https://www.kegg.jp/).   2. In the search bar, enter the name or KEGG ID of the microorganism. If the microorganism's name is unknown, try searching by its genus or other relevant identifiers.   3. Click the search button, and the system will display results based on your input.   4. On the search results page, you will see a list of strains or species re......

• • How Can the Metabolic Pathways of a Specific Species Be Identified Using KEGG?

  To identify the metabolic pathways of a specific species using KEGG (Kyoto Encyclopedia of Genes and Genomes), the following steps can be followed:   1. Access the KEGG database at https://www.kegg.jp/ and navigate to the "Pathway" section.   2. Enter the name of the target species (e.g., Homo sapiens) in the search bar.   3. Click the "Search" button to retrieve metabolic pathway data associated with the species.   4. The results page will display various categories of metabolic pathways, such as car......