Ingenuity Variant Analysis
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Application data |
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| Created by | Ingenuity Systems |
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| Biological application domain(s) | Genomics, Exome, Whole genome resequencing, SNPs |
| Principal bioinformatics method(s) | Variant classification |
| Technology | Any |
| Created at | Ingenuity Systems |
| Maintained? | Maybe |
Summary: Ingenuity Variant Analysis is a web application that helps researchers studying human disease to identify causal variants
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Description
Ingenuity Variant Analysis is a web application that helps researchers studying human disease to identify causal variants from human resequencing data in just minutes. Ingenuity Variant Analysis combines analytical tools and integrated content to help you rapidly identify and prioritize variants by drilling down to a small, targeted subset of compelling variants based both upon published biological evidence and your own knowledge of disease biology. With Variant Analysis, you can interrogate your variants from multiple biological perspectives, explore different biological hypotheses, and identify the most promising variants for follow-up.
Highlights:
- Leverage a single application that accesses multiple sources of content to rapidly and comprehensively prioritize variants (including SNV, indels, structural, and CNVs)
- Rapidly identify variants across the genome that are known to be deleterious based upon literature evidence (not just predictions)
- Choose promising variants for follow-up based on detailed annotations and facts from the literature about implications of known variants and genes containing novel variants on disease biology
- Use knowledge of causal regulation relationships to discover compelling hypotheses for the impact of variants on disease progression
- Integrate your own data (such as RNA-Seq isoform expression data or epigenetic genome coordinate data) to refine your variant analysis
- Leverage disease models that including symptoms, signaling pathways, cellular processes, established disease genes and efficacious drug targets to rapidly identify disease driver mutations
- Integrate pharmaceutically relevant content (drug targets and variants implicated in drug response, metabolism, and toxicity) to more rapidly prioritize variants based on pharmacogenomics
- Use hereditary relationships and inheritance patterns to identify variants that contribute to disease progression across multiple samples, ranging from a few to hundreds all at once
Links
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