Category Archives: General statistical genetics principles

Top 10 Posts for Understanding Clinical Annotation of Genomic Variants

Top 10

The VarSeq clinical platform is built on a strong foundation of data curation and annotation algorithms to ensure the variants identified have all the information required to make the correct clinical assessments.  It’s easy to make light of “variant annotation”, but the details run very deep into the roots of how we represent genomic data, how public data is aggregated, stored… Read more »

SVS, Population Genetics, and 1000 Genomes Phase 3

One frequent question I hear from SVS customers is whether whole exome sequence data can be used for principal components analysis (PCA) and other applications in population genetics. The answer is, “yes, but you need to be cautious.” What does cautious mean? Let’s take a look at the 1000 Genomes project for some examples.

Genomic Prediction and How it’s Used

Golden Helix is excited to host a webinar on Tuesday August 26th discussing the Genomic Prediction methods which were recently integrated into the SVS software. Genomic prediction uses several pieces of information when calculating its results. Genetic information is used to predict the phenotype or trait for the individuals. The phenotypic trait data can be provided for a subset or for all… Read more »

RefSeq Genes: Updated to NCBI Provided Alignments and Why You Care

You probably haven’t spent much time thinking about how we represent genes in a genomic reference sequence context. And by genes, I really mean transcripts since genes are just a collection of transcripts that produce the same product. But in fact, there is more complexity here than you ever really wanted to know about. Andrew Jesaitis covered some of this… Read more »

Population Structure + Genetic Background + Environment = Mixed Model

A few months ago, our CEO, Christophe Lambert, directed me toward an interesting commentary published in Nature Reviews Genetics by authors Bjarni J. Vilhjalmsson and Magnus Nordborg.  Population structure is frequently cited as a major source of confounding in GWAS, but the authors of the article suggest that the problems often blamed on population structure actually result from the environment… Read more »