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 »
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 »
Genome-wide association studies (GWAS) are useful in genetics as they test for the association of a phenotype with common genetic variants. GWAS is “hypothesis-free” and does not require prior knowledge of a gene’s biological impact on a trait. The catch though is that this leads to analyzing hundreds to thousands of genome-wide array samples to elucidate single nucleotide polymorphisms (SNPs) associated with a specific phenotype.
Give our SVS viewer a try today! Interested in seeing what the SNP & Variation Suite (SVS) software can do? Download the free SVS Viewer! With the SVS Viewer, you can explore and interact with the workflows of a pre-built projects. To get you started, we have included a SNP GWAS project for you to download. And don’t worry, it is… Read more »
The 65th annual ASHG in Baltimore will be another exciting one. We at Golden Helix have been very busy this year making great improvements to both SVS and the VarSeq software and we look forward to showcasing them during our in-booth demos. In particular, we will launch two new additions to the VarSeq software suite; VSReports and VSWarehouse. VSReports brings highly customizable clinical… Read more »