Category Archives: Best practices in genetic analysis

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 »

Solving the Eigenvalue Decomposition Problem for Large N

Eigenvalue Decomposition

Solving the Eigenvalue Decomposition Problem for Large Sample Sizes Since our introduction of the mixed model methods in SVS, along with GBLUP, we have been very pleased to see it used by a number of customers working with human and agri-genomic data. As these customers have grown their genomics programs, the number of samples they have for a given analysis… Read more »

N-of-One Integration comes to VSReports

Update_fi

Submit directly to N-of-One from VarSeq If you or your lab uses N-of-One solutions for clinical annotations, here’s some good news: You can now submit directly to N-of-One from VarSeq! N-of-One’s set of preferred transcripts may differ from those outputted by our algorithms in VarSeq, so our solution was built with that in mind. Our slick, easy to use, and… Read more »

Concepts and Relevance of GWAS

Genome-Wide Association Studies

Concepts and Relevance of Genome-Wide Association Studies Genome-Wide Association Studies continue to be a very effective method for determining the underlying cause of disease, Golden Helix is happy to share our long-standing knowledge with the community. We are very happy to announce that “Concepts and Relevance of Genome-Wide Association Studies”, a paper surrounding GWAS was recently published in Science Progress… Read more »

Quality Assurance Sample Statistics Added To VarSeq

VarSeq

As VarSeq continues its adoption amongst clinical labs and researchers looking for reproducible workflows for variant annotation, filtering and interpretation, we have continued to prioritize the addition of features to assess the quality of the upstream data at a variant, coverage and now sample level. The  Importance of Quality Assurance Sample prep and sequencing problems are difficult to detect through the analysis… Read more »