GenomeStudio Software

The graphical display of genotypes in GenomeStudio is a Genoplot, with data points color coded for the call (red = AA, purple = AB, blue = BB). Genotypes are called for each sample (dot) by their signal intensity (norm R) and Allele Frequency (Norm Theta) relative to canonical cluster positions (dark shading) for a given SNP marker.

The GenomeStudio Genotyping (GT) Module supports the analysis of Infinium and GoldenGate genotyping array data. This module enables efficient genotyping data normalization, genotype calling, clustering, data intensity analysis, loss of heterozygosity (LOH) calculation, and copy number variation (CNV) analysis. Fully integrated with the Infinium LIMS server, the GT Module allows you to access data and manage projects directly from within GenomeStudio.

As in all GenomeStudio modules, the GenomeStudio Framework displays data output in tabular form and enables you to visualize your results quickly and easily using the Illumina Genome Viewer and Illumina Chromosome Browser graphical tools.

GT Module Highlights

• Analyze SNP and CNV data across 5 million markers
• Estimate Log R ratio and B-allele frequency for copy number analysis
• Call genotypes, normalize and cluster data, and generate SNP statistics
• Export genotype data to various third party applications; access multiple CNV algorithms and copy number variation analysis tools
• Generate a chromosomal heat map for examining copy number aberrations across the entire genome for multiple samples
• Analyze data from two different product versions within the same project

This GenomeStudio heat map dendrogram clusters rows (Target ID) and columns (Differential Scores). Using the Heat Map tools in the GenomeStudio Gene Expression Module enables easy visualization and analysis of large amounts of data.

The GenomeStudio Gene Expression (GX) Module supports the analysis of Direct Hyb and DASL expression array data. It enables the visualization of differential mRNA and microRNA expression analysis as line plots, histograms, dendrograms, box plots, heat maps, scatter plots, samples tables, and gene clustering diagrams. Simplified data management tools in GenomeStudio Software include hierarchical organization of samples, groups, group sets, and all associated project analysis.

As in all GenomeStudio modules, the GenomeStudio Framework displays data output in tabular form and enables you to visualize your results quickly and easily using the Illumina Genome Viewer and Illumina Chromosome Browser graphical tools.

GX Module Highlights

• Analyze differential expression using gene-level statistical analysis tools
• Visualize results as line plots, histograms, dendrograms, box plots, heat maps, scatter plots, samples tables, and gene clustering diagrams
• Simplify data management for hierarchical organization of samples, groups, group sets, and project analysis
• Identify fold-level changes, perform T-test and ANOVA, and compare results across different sample group sets
• Combine and merge gene expression data with DNA methylation and miRNA profiling data within the same project
• Export whole-genome expression and genotyping data to various third party tools for eQTL analysis

The GenomeStudio Methylation (M) module supports the analysis of Infinium and GoldenGate methylation array data. This module calculates methylation levels (beta values) and analyzes differential methylation levels between experimental groups. It enables you to view CpG island methylation status across the genome with the llumina Genome Browser and Illumina Chromosome Browser.

Single-site resolution data can be visualized as line plots, bar graphs, scatter plots, histograms, dendrograms, box plots, or heat maps. This module also enables you to combine methylation data with gene expression profiling experiments within the same GenomeStudio project for correlation between levels of methylated sites (beta values) and differential gene expression levels (p values).

Methylation Module Highlights

• Calculate methylation levels and visualize CpG island information
• Analyze differential methylation levels between two experimental groups
• Visualize results as line plots, bar graphs, scatter plots, histograms, dendrograms, box plots, heat maps, or control summary reports
• Merge gene expression profiling data with methylation data in the same project
• Display whole-genome data and beta values within the Illumina Genome Viewer
• Visualize beta values for one or more samples in the Illumina Chromosome Browser

The Polyploid Genotyping Module supports genotyping data analysis of polyploid organisms such as wheat and potato. It uses two density clustering algorithms to assign samples to meaningful clusters: PolyGentrain and Density Based Spatial Clustering of Applications with Noise (DBSCAN).

Polyploid Genotyping Module Highlights

• Call as many clusters as desired, enabling studies of hexaploid or octoploid species
• Automate clustering and genotyping calling for polyploid organisms