Tag Archives: genomic prediction

Optimized Breeding Selection via Genomic Prediction

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 »

Genomic Prediction Methods in SVS Q&A

VS-CNV Annotations

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 »

Cross-Validation for Genomic Prediction in SVS

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 »

Q&A from our December Genomic Prediction webcast

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 »

What to expect from Golden Helix in 2015

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.