Author Archives: Golden Helix

GxE Regression Option to be Available in SVS

We are pleased to announce that another one of the most asked for features is going to be a part of our SNP & Variation Suite™ software, Gene by Environment Interaction Regression (also known as GxE Regression). Earlier this year other highly asked for features were added to SVS including applying a prediction model to a new dataset, cross-validation for… Read more »

Coverage Statistics Come to VarSeq

A prerequisite for clinical NGS interpretation is ensuring that the data being analyzed is of high enough quality to support the test results being returned to the physician. The keystone of this quality control process is coverage analysis. Coverage analysis has two distinct parts. Ensure that there is sufficient coverage to be confident in called variants Make certain that no… Read more »

Quality Assurance: Is it a Boy or Girl?

A common question that comes through support is if there are options in SVS for doing gender inference or checks. There is indeed functionality in SVS for this QC check!  This function is under the Genotype Menu for Sample Statistics; there are a lot of great statistics available to check the quality of your data in SVS, but I’ll walk… Read more »

The 10th Anniversary of GWAS

      Golden Helix    July 30, 2015    No Comments on The 10th Anniversary of GWAS
10th Anniversary of GWAS

GWAS became possible about 10 years ago as the result of several scientific advances. Since then, GWAS has continually developed as a primary method for identification of disease susceptibility genes in humans and other organisms. At Golden Helix we are proud of our history in supporting GWAS analysis from its inception. Our software was used to analyze whole-genome data from… Read more »

Meta-Analysis is now available in SVS!

Earlier this spring we announced that Meta-Analysis was coming to SVS very soon. Now, I am pleased to announce that it is available in the latest release of SVS (version 8.4.0). Meta-Analysis takes the results of two or more GWAS studies for multiple SNPs or markers, and standard meta-analysis statistics are then performed on each SNP and the results compiled into… Read more »