SOPHiA Clinical Exome Solution v3
Dedicated features to ease variant interpretation
The SOPHiA DDM™ platform features intuitive variant filters and prioritization options to streamline the interpretation process and help you greatly reduce turnaround time.
- Dual Variant Pre-classification to improve assessment of variants pathogenicity based on both ACMG scores and our machine learning-based predictions
- Virtual Panel to restrict the interpretation to sub-panels of genes using the HPO or OMIM browser
- Cascading Filters to apply custom filtering options for quicker screening of relevant variants and save strategies for future analyses
- Familial Variant Analysis to quickly identify causative variants by selecting different inheritance modes with a single mouse click to shorten the candidate variant list accordingly
Through SOPHiA DDM™, you can also have access to Alamut Visual Plus, a full-genome browser that integrates numerous curated genomic and literature databases, guidelines, missense and slicing predictors, thus enabling a deeper variant exploration.
Full coverage of the mitochondrial genome coupled with sensitive variant calling
The probe design is highly optimized to guarantee high on-target reads percentage and coverage uniformity even in GC-rich regions, including the first exon. With SOPHiA Clinical Exome Solution v3, you get full mitochondrial genome variant detection, including non-coding variants, now in 280 genomic locations. Additionally, with improved analytical performance, you can reach more than 90% analytical sensitivity for CNV detection*.
|Addressed Diseases||Rare and inherited disorders|
Entire mitochondrial genome
~ 200 non-coding variants with known pathogenicity in deep introns/enhancer/promoter genes
|Target Region Size||16 Mb|
|DNA Input Amount||200 ng|
|Library Preparation Time||1.5 days|
|Analysis Time From FASTQ File||Overnight|
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(*Data on file. Results may vary. Sensitivity of CNV detection in two consecutive regions (exons) with 40 million fragments (80 million reads) based on internal data.)