Thank you to those who attended our recent webcast by Gabe Rudy, Large Scale PCA Analysis in SVS. For those who could not attend, you can find a link to the recording here. While this webcast discussed methods for principal components analysis (PCA) in SVS, including the new capability for performing principal components analysis on large sample sizes, it also… Read more »
SVS 8.9.0 was released on August 19th and features a new GBLUP by Bin feature and a new utility to find the LD scores of markers and categorize them into bins, along with several mixed-model upgrades and many other upgrades, fixes, and polishes. The two new features LD Score Computation and Binning and Compute GBLUP Using Bins, while they can… Read more »
Using the K-Fold Cross-Validation Statistics to Understand the Predictive Power of your Data in SVS In cross-validation, a set of data is divided into two parts, the “training set” and the “validation set”. A model for predicting a phenotype from genotypic data and (usually) some fixed effect parameters is “trained” using the training set—that is, the best value(s) of the… Read more »
