Bioinformatics Analysis FAQ

• • How to Generate an OPLS-DA Plot Using SIMCA 13?

  SIMCA is a specialized software for statistical analysis, widely used in multivariate data analysis, including orthogonal partial least squares discriminant analysis (OPLS-DA). The following steps outline the general procedure for generating an OPLS-DA plot:   1. Data Preparation Ensure that the dataset is appropriately formatted. This typically involves organizing variables (e.g., chemical components, physical properties) in a structured table, along with one or more categorical variables to classify......

• • How Can the Lack of Significant Pathway Enrichment (p > 0.1) in Proteomic KEGG Analysis Be Resolved?

  In KEGG enrichment analysis of proteomic data, when all p-values exceed 0.1, it suggests that no significantly enriched pathways have been identified within the analyzed protein set. This issue may arise due to several factors:   1. Insufficient Sample Size A small sample size reduces statistical power, making it challenging to detect significant pathway enrichment.   2. Quality of the Protein List The input protein list may be incomplete or biologically irrelevant.   3. Selection of the Background Ge......

• • What Does Each Letter Represent in the COG Database? Is "mot" a Subcategory of "M" in COG Annotation?

  In the Clusters of Orthologous Groups (COG) classification system, each letter corresponds to a specific functional category:   INFORMATION STORAGE AND PROCESSING [J] Translation, ribosomal structure, and biogenesis [A] RNA processing and modification [K] Transcription [L] Replication, recombination, and repair [B] Chromatin structure and dynamics   CELLULAR PROCESSES AND SIGNALING [D] Cell cycle control, cell division, chromosome partitioning [Y] Nuclear structure [V] Defense mechanisms [T] Signal tr......

• • How to Interpret KEGG Analysis Results?

  Following KEGG analysis, a results table and a pathway diagram are generated. These outputs provide critical insights into the functional significance of the identified differentially expressed genes.   Understanding the KEGG Pathway Table 1. Pathway Name Lists the biological pathway name associated with the gene set.   2. Pathway ID Provides a unique identifier for each pathway (e.g., hsa04110, corresponding to the human cell cycle pathway).   3. p-value Represents the statistical test result, reflec......

• • How to Identify Important Variables After Principal Component Analysis?

  After performing Principal Component Analysis (PCA), it is essential to determine which original variables contribute the most to the principal components, thereby identifying the most influential variables. This can be achieved through the following steps:   Examine the Explained Variance Ratio of Principal Components PCA generates a set of principal components, each representing a linear combination of the original variables. The explained variance ratio quantifies the proportion of total variance c......

• • How Do Principal Component Analysis (PCA) and Factor Analysis (FA) Differ?

  Principal Component Analysis (PCA) and Factor Analysis (FA) are widely used multivariate statistical techniques for dimensionality reduction and extracting key information from data. Although both methods reduce data dimensionality, they differ in their objectives, underlying assumptions, and applications. The following outlines the key distinctions between PCA and FA:   Principal Component Analysis (PCA) 1. Objective PCA aims to transform original variables into a set of uncorrelated principal compon......

• • How Can the Precursor Protein Be Identified After Peptide Sequencing? Which Software Tools Are Available?

  After identifying a peptide sequence, assigning it to its corresponding precursor protein typically involves the following steps:   1. Database Search The peptide sequence is searched in established protein databases such as UniProt, NCBI, and Swiss-Prot to identify potential precursor proteins. This is the most commonly used approach, in which experimentally derived peptide sequences are compared against protein sequence databases to find the most likely matches.   2. Computational Tools for Peptide-......

• • How to Conduct a Simple GO Annotation Analysis?

  A simple Gene Ontology (GO) annotation analysis can be performed by following these steps:   1. Prepare a Gene List Start with a list of genes of interest, such as differentially expressed genes obtained from transcriptome sequencing.   2. Select an Online Analysis Tool Several bioinformatics tools are available for GO annotation and enrichment analysis. Commonly used tools include: (1) DAVID (Database for Annotation, Visualization and Integrated Discovery): A widely used platform that supports GO enr......

• • How to Understand Principal Component Scores in Principal Component Analysis?

  Principal component scores represent the coordinates of each sample in the principal component space. They provide insights into the sample’s position and its relative contribution to each principal component. A higher principal component score indicates a stronger projection of the sample onto that principal component, signifying greater alignment with the corresponding variance direction.   Interpretation as New Coordinates Principal component scores can be interpreted as the coordinates of each dat......

• • Which Online Tools Can Compare Antibody Heavy and Light Chain Variable Region Sequences?

  Several specialized bioinformatics tools and databases can be used to align and compare the variable region sequences of antibody heavy and light chains. These platforms not only facilitate sequence alignment but also provide structural and functional insights into antibodies. Below are commonly used tools:   IMGT (International ImMunoGeneTics Information System) 1. Description IMGT/V-QUEST is a dedicated tool for immunoglobulin (Ig) and T cell receptor (TCR) sequence analysis. It allows alignment of ......