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Exemplar Analytics is being used by leading researchers at many of the top 20 Pharmaceutical, Biotech and Non-profit research centers in the world. With the most extensive set of features covering both traditional association analysis and complex genetics, Exemplar can fulfill any researcher's needs for analyzing Genotyping Data. With the future in mind, Exemplar was designed for scalability to ensure that it can process thousands of samples with 1 million + markers that will become the standard for Genome Wide Association studies. |
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Data Import
- Auto import of Affymetrix CHP\CEL file
- Illumina BeadStudio integration via plug-in
- ABI Genemapper import
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Data Presentation
- Powerful Graphics and Extensive Annotations
- Import genotyping analysis results from any third party tool
- Backed by pre-populated genetics database with info from NCBI dBSNP, NCBI Gene and Gene Ontology
- View results from different tools/methods/platforms graphically side-by-side on our powerful Whole Genome Viewer
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Data Analysis
- 20+ Association Statistics with multiple testing corrections
- Identify insertions/deletions in the genome
- Predict quantitative traits from genetic and non-genetic factors
- Combine genetics and covariates to predict outcomes
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Functional Genomics
- Map significant SNP's automatically to related genes and ontology's
- View interactive graphical display of Gene Ontology hierarchy.
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Additional Details |
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Data Import
- Affymetrics 10K, 100K, 500K
- Affymetrics Gene Chip Compatible
- Direct CHP file import
- Recognition of all dbSNP markers
- Full support for custom arrays
- Wizard-driven import capability
Data Analysis
- Extensive built in Statistics
- Whole genome sliding window haplotype analysis for association
- 15+ core association statistics
- The fastest permutation corrections for 500K+ markers and 1000+ samples.
- Identify Insertions\Deletions in the Genome
- Built in Copy Number analysis
- Loss of Heterozygosity analysis
- Analyze unlimited Quantitative Traits
- ANOVA, Linear and Multiple Regression
- Combine Genetic and Non-Genetics Factors To Predict Outcomes
- Include covariates like “age”, “gender” and “smoking status” in analysis.
- Build multi-marker models in combination with covariates
- Chi Square, odds ratio, Fishers extract, etc.
- EM Algorithm for haplotype based analysis
- Linkage disequilibrium, D', R2, etc.
- Machine learning for multi-loci models
Data Presentation
- Graphical Chromosome Viewer
- Positional Display of SNP's / Associated Genes
- Haplotype and LD Interactive Grid
- Hyperlinking to NCBI, Gene Ontology, etc.
- Histograms and Scatterplots by Chromosome
- Full Genomics Database (dbSNP, Human Genes)
Functional Genomics
- Integrated Gene Ontology Database
- Automatic GO Mapping of SNP's
- Graphical Display of GO Hierarchy
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