Thank you to everyone who joined us for our webcast on the upcoming VarSeq features supporting the full spectrum of genomic variation! Traditionally, NGS cancer testing started with small gene panels that looked at a small set of the most common genes to identify small mutations, such as BRAF V600E. However, there are many classes of mutation that cannot be… Read more »
Our recent release of VarSeq 2.2.2 comes with a long list of upgrades and new features. In this blog post, we will demonstrate how defining sample phenotypes are available in VSClinical. One noticeable change is the ACMG guideline variant evaluation in VSClinical. Not only has this interface added CNV guideline evaluation, simplified the reporting process with embedded Microsoft Word and… Read more »
In this blog post, I will be analyzing a loss-of-function splice variant in MTHFR using VarSeq. In the search for clinically relevant variants contributing to rare disorders, efficient filtering strategies are an important step in eliminating disinteresting variants. However, any applied filters must also ensure no interesting variants inadvertently get filtered out. Golden Helix provides the tools to complete this… Read more »
SVS is a project-oriented program that manages and analyzes genomic datasets. This webcast statistically and visually explores the relationships among genetic variants within a cattle dataset. Even further, this webcast evaluates genotypes with corresponding phenotypes to assess how well a model can predict a phenotype of interest. Starting with genotypic data from the microarray and the recorded phenotypic data for… Read more »
What is Genomic Prediction? Genomic prediction is an algorithm widely used to improve desirable phenotypic traits in agriculture. For example, the cattle industry uses genomic prediction to improve beef quality and palatability as well as improve dairy production (1,2). By using genomic prediction, researchers can minimize multiple expenses in breeding industries as well as diminish the need for performing cumbersome… Read more »
Yesterday’s webcast, Genomic Prediction Methods in SVS, gave attendees a chance to see how the principles of genomic prediction are applied within SVS, predicting phenotypes for both plant and animal species. You can find a recording of the webcast on our site here should you be interested in checking it out or sharing with a colleague! The webcast garnered a… Read more »
The SNP and Variation Suite (SVS) software currently supports three methods for genomic prediction: Genomic Best Linear Unbiased Predictors (GBLUP), Bayes C and Bayes C-pi. We have discussed these methods extensively in previous blogs and webcast events. Although there are extensive applications for these methods, they are primarily used for trait selection in agricultural genetics. Each method can be used… Read more »
Our Genomic Prediction webcast in December discussed using Bayes-C pi and Genomic Best Linear Unbiased Predictors (GBLUP) to predict phenotypic traits from genotypes in order to identify the plants or animals with the best breeding potential for desirable traits. The webcast generated a lot of good questions as our webcasts generally do. I decided to begin to share these Q&A… Read more »
There is a lot we can be grateful for at Golden Helix. The past year was marked by two major breakthrough launches. Earlier in 2014, we shipped SVS 8 which unified SVS with our GenomeBrowse product. We were able to improve SVS’ data management and visualization capabilities. In addition we added a number of new methods in SVS, such as SKAT-O, MM-KBAC, and various genomic prediction algorithms.
