EgyGene GelAnalyzer4

EgyGene GelAnalyzer4 analyzes one-dimensional gel electrophoresis images to detect lanes and bands, quantify DNA/RNA/protein, detect molecular markers from pre-analyzed data, compute similarity percentages using fourteen equations, and construct UPGMA phylogenetic trees to support genetic variation and population analyses.

Key Features:

• Gel Image Enhancement: Enhances clarity and color contrast of gel images for improved analysis.
• Lane and Band Detection: Performs both automatic and manual detection of lanes and bands within gel images.
• Data Merging: Merges data from multiple analyses of different samples or gels into a single comprehensive table.
• Molecular Marker Detection: Detects molecular markers from pre-analyzed data using user-defined criteria.
• Phylogenetic Tree Construction: Constructs phylogenetic trees using the unweighted pair group method with arithmetic mean (UPGMA) and computes similarity percentages using Anderberg, Czekanowski, Dice, Faith, Gower and Legendre, Jaccard, Nei and Li, Rogers and Tanimoto, Russel and Rao, simple matching, Sokal and Michener, Sokal and Sneath 1, Sokal and Sneath 2, and Sorensen equations.
• Population Parameters Estimation: Calculates population parameters from pre-analyzed images to assess genetic diversity and structure.
• Analytical Outputs: Produces relative mobility values, molecular weight/size estimates, quantification of DNA/RNA/protein, band presence/absence tables, polymorphism percentages, similarity percentages, phylogeny, and population parameters.
• Lane and Band Editing and Comparison: Supports modification of lane order and splitting/merging of lanes and bands and comparison across analyzed images.
• Annotation: Annotates sample names and detected markers directly on gel images.

Scientific Applications:

• Gel electrophoresis analysis: Analysis and quantification of DNA, RNA, and protein bands from one-dimensional gels.
• Molecular marker identification: Detection and characterization of molecular markers and polymorphisms using user-defined criteria.
• Phylogenetic inference: Construction of UPGMA trees using multiple similarity metrics to infer relationships among samples.
• Population genetics: Estimation of population parameters and assessment of genetic diversity and structure.
• Comparative analyses: Merging and comparative analysis of datasets across multiple gels and experiments.

Methodology:

Enhancement of gel image clarity and color contrast; automatic and manual detection of lanes and bands; merging of analysis results from multiple samples/gels; detection of molecular markers from pre-analyzed data using user-defined criteria; calculation of relative mobility, molecular weight/size estimates, and quantification of DNA/RNA/protein; generation of band presence/absence tables and computation of polymorphism and similarity percentages; estimation of population parameters; and construction of UPGMA phylogenetic trees using similarity percentages computed with Anderberg, Czekanowski, Dice, Faith, Gower and Legendre, Jaccard, Nei and Li, Rogers and Tanimoto, Russel and Rao, simple matching, Sokal and Michener, Sokal and Sneath 1, Sokal and Sneath 2, and Sorensen equations.