Advanced genomic analysis for crop improvement and breeding programs. Analyze genetic diversity, population structure, and kinship relationships with ease.
Industry-standard tools for comprehensive population genomic analysis
PCA Analysis Visualization
Example scatter plot showing genetic clusters
Principal Component Analysis (PCA) reduces the dimensionality of your genomic data to reveal hidden patterns and population stratification. Perfect for visualizing genetic relationships and identifying distinct clusters in your breeding populations.
K-means clustering automatically identifies distinct genetic groups in your data. Uses silhouette scoring to determine optimal cluster numbers and provides detailed cluster assignments for each sample.
Clustering Visualization
Example showing distinct genetic groups
Kinship Matrix Heatmap
Example relatedness matrix visualization
Calculate identity-by-state (IBS) or genomic relationship matrices (GRM) to assess relatedness between samples. Essential for breeding programs and understanding population dynamics.
Get from data to insights in three easy steps
Upload your VCF or CSV files securely to our cloud platform
Choose your analysis type and let our algorithms do the work
View interactive visualizations and download publication-ready results
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