In recent years, most labs have moved SNP analysis from array-based techniques to NGS. Now it’s time to do the same for CNV analysis. While array-CGH has long been the most popular method used to detect pathogenic CNVs and the first tier genetic test for many diseases, its resolution is relatively low. Most platforms used in diagnostic labs are only able to detect CNVs of approximately 20,000 base pairs in size or larger. Since the majority of CNVs in the human genome are smaller, this means that array-based methods are unable to detect about 80% of all human CNVs. Amongst these missed CNVs, there may be pathogenic changes.
Moving to NGS-based CNV detection can solve this problem. CNVs as small as 100 base pairs can be detected by NGS. At this resolution, about 7,000 CNVs can be called in a typical human genome, thousands more than would be obtained from an array analysis. Our cloud-based CNV analysis software, InHelix, has been designed from the ground up to handle the large amount of data generated by genome-wide NGS-based CNV detection. The software makes it easy to annotate, filter, visualise and report CNVs. And thanks to InHelix’s advanced ranking algorithm, the most relevant CNVs will always be at the top of the list.
InHelix can import duplications and deletions from several of the most popular CNV callers, including CNVnator, Pindel, CoNIFER, Control-FREEC, CoNVaDING, CNVkit, Illumina’s Canvas and others.
InHelix uses a multitude of data sources to annotate CNVs, such as DGV, dbVar, DECIPHER, ClinVar, OMIM, dbSNP, UCSC and NCBI. The number of data sources is quickly expanding.
For smaller CNVs, it becomes particularly useful to know their exact impact on the gene region, such as which exons are deleted and whether UTRs are included in the CNV. InHelix offers clear visualisations of the affected gene region.
Thanks to InHelix’s charts, you can easily check key metrics of the CNV calling. This includes the percentage of deletions vs. duplications, the regions most affected by CNVs, and the CNV size distribution.
InHelix comes with 80 in silico panels, ranging from Ataxia to Zellweger Syndrome. These panels are curated and kept up to date by Diploid’s team of geneticists, reducing the risk of missing relevant CNVs due to outdated panels. In addition, you can easily add your own panels and share them with lab members.
To our knowledge, InHelix is the only software that can perform a CNV family analysis. This is an important advantage as comparison among family members is the most powerful NGS filter. The software is not limited to trio analysis - it can handle any family configuration.
In addition to traditional panels, InHelix also includes an innovative way to integrate the latest scientific findings into your CNV analysis. On a weekly basis, InHelix mines the literature for gene-phenotype correlations, and automatically updates its knowledge base. Simply enter HPO terms to describe your patient’s phenotype and InHelix will generate a unique panel of genes most relevant to the individual patient.
InHelix brings Diploid’s critically acclaimed reports to your lab. Shortlisted CNVs will automatically be added to the report, including visualisations. References can be easily added from PubMed. All CNV details are automatically hyperlinked, allowing the report’s recipient to verify CNV filtering and ranking.
We take data security very seriously. That’s why we are hosting InHelix at one of the world’s most secure data centres. Our data centre is ISO 27001 certified, HIPAA-compliant and has repeatedly passed SAS70 Type II audits.
InHelix offers an API to import and annotate cases. This makes it possible for bioinformaticians to connect your current CNV calling pipeline to InHelix, and upload the called CNVs directly from apps like CNVnator. The API allows InHelix to integrate with high throughput pipelines for NGS-based diagnostics.
Spend a few minutes with a friendly member of our team and we’ll answer all your questions and share everything you need to know about working with InHelix.Schedule a call