The Science of iVariantGuide

Figure 1: A Typical Variant Analysis Pipeline.
There are many pipelines and workflows that can take your sequence data from FastQ/FastA to a variant call file or .vcf as shown in Figure 1. The question for most becomes what do you do then? A vcf file is essentially a large spreadsheet with all the variants identified in the sample. Some are annotated with effect predictions, allele frequency, etc. and some are not. This type of analysis is called tertiary analysis and one of the hardest parts about this type of analysis is that there is no one way to go about it – despite all the demos you watch. When it comes to variant interpretation, one-size does not fit all.

Figure 2: iVariantGuide’s interactive graphic filters let you explore relationships that would otherwise get lost.
iVariantGuide takes your vcf file and will ensure it is annotated with multiple sources and then provides a number of interactive filters for you to see relationships between various biological features and/or effects. With other variant analysis or interpretation applications, you must know exactly the tradeoff you are making when selecting your filters to go from 100,000+ variants to a manageable list of a few, 50, or whatever number of variants fits your criteria. With iVariantGuide, we let you explore these tradeoffs in real-time with intuitive filters that update immediately. This lets you explore relationships like those that may exist between pathogenic variants and chromosomal locations.
VariantGuide gives you simple and easy tools to save sets of filters (presets) and apply them to other samples. You can even share your filter preset and analysis with others simply by entering their email address.
Once you have filtered your vcf to your “Variants of Interest” the question becomes, “Now what?” That where iVariantGuide opens a new window to variant interpretation by allowing you see which pathways and GO terms are most enriched with you variants. But we go a step further and provide you advanced pruning algorithms (Alexa et al 2006) that eliminate many of the false positives associated with GO analyses. This advanced analysis capability lets you quickly form hypotheses about functional relationships between observed variants and impacts on biological processes, pathways, molecular functions, and cellular components. Check out our several publications on the use (and misuse) of GO analysis.
iVariantGuide lets you go from vcf to actionable interpretation in minutes and provides unique visualization to help you make sense of the data and plan your next experiment.