New in emedgene 2.24-2.25 (Aug 11, 2021)

mtDNA variants are here! ✨

You can now analyze and interpret mtDNA variants on the emedgene platform, using a streamlined workflow that makes it easy to focus your analysis on the clinically meaningful variants.

mtDNA variant callers

Our secondary analysis pipeline uses DRAGEN and leverages improved quality metrics to help reduce the number of variants for review,
We also support VCF files from mity, MuTect, and CNVkit.

mtDNA variant filter

You can focus on mtDNA variants by using the updated mtDNA filter in the Variant Type Filters. The filter can be added to your custom presets.

mtDNA variant annotation

The Variant table and Variant page reflect basic mtDNA variant annotations including:

genes,
transcripts,
population annotations (gnomAD and MITOMAP),
Missense Prediction scores (APOGEE and MitoTIP),
known disease-causing variants (MITOMAP).

mtDNA variant classification

The ACMG SNV Classification wizard is now available for tagged mtDNA variants. It utilizes only relevant ACMG criteria and automatically defines the resulting ACMG class based on the manually assigned criteria.

Related Cases is a new section of the Variant page that highlights information on previous variant curation activity (i.e., assigning a variant tag and/or assigning Pathogenicity and/or adding Variant Interpretation notes).

Stay tuned for the curated data sharing between partner organizations!

Add virtual variants

You can now manually add variants not present in the VCF or not called from FASTQ to your case. This is useful when:

you need to complement NGS with data from other genetic tests (long-read sequencing, optical mapping, CGH, SNP array, karyotyping/FISH, repeat-primed PCR, MLPA, Southern blot, etc);
you want to report a few adjacent variants as a single multi-nucleotide variant.

Supported variant types are SNV, CNV, UPD, ROH, and STR. SV is coming soon!

CNV calling from exomes

We now support CNV calling from exome data using DRAGEN. High precision and recall are achieved through a lab-optimized panel of normals (PON). Results vary per laboratory/sample preparation protocol, and validation is performed upon request.