Category Archives: Clinical genetics

Annotating Cancer Mutations with CIViC

      Gabe Rudy    November 15, 2016    2 Comments on Annotating Cancer Mutations with CIViC
CIViC database

While clinical assessments of germline mutations have been collected in ClinVar under the stewardship of the NCBI and the collaborate effort of many testing labs, the same type of resource has been missing for mutations that could informal clinical care in Cancer. Or at least, that is what I thought until I started to work with CIViC. With the stewardship of… Read more »

Why Call CNVs: Getting More from your NGS Data

CNV Call

Copy Number Variants have been important to clinical genetics for quite a while now. So, what has made now the right time to be looking at calling CNVs from NGS data? Well, there are a number of good reasons. The dominant one is simply that the NGS data you are already creating for calling variants can be used in many cases… Read more »

CADD, OMIM and OncoMD Coming to SVS

CAD, OMIM and OncoMD

For our upcoming SVS 8.6.0 release, we’ve updated our Annotate and Filter Variants feature to utilize our powerful VarSeq annotations. Annotations can be run against gene, interval, variant, and tabular tracks, including RefSeq, ClinVar, CADD, OMIM and OncoMD. The new streamlined dialog allows users to select track specific options and to set up custom filters. While our public annotation repository… Read more »

NGS-based Clinical Testing (Part I)

NGS Testing

The adoption of genetic services is key to our ability to provide personalized medicine in the future. The goal is to better diagnose diseases, predict their outcome, and choose the best possible care option for a patient. We still have a long way to go to achieve this goal. While there is agreement about the ultimate goal, there is still… Read more »

CADD Scores: Rank and Filter in Harmony!

CADD Score

There used to be much energy expended at conferences, bioinformatics forums and even publications about what was the better strategy for interpreting variants of clinical significance: Rule-based filtering and classification mechanisms or rank-based prioritization through all-encompassing “pathogenicity” scores. Both have shown to be effective. Rule-based systems, as exemplified in this filtering diagram in Baylor’s ground-breaking paper on clinical whole-exome sequencing… Read more »