Author Archives: Golden Helix

Conference Report: International Genetic Epidemiology Society and Genetic Analysis Workshop

The week of October 10-16th was a busy time in our industry.  Hundreds of biostatisticians, genetic epidemiologists, and statistical geneticists gathered in Cambridge, MA for the annual conference of the International Genetic Epidemiology Society (IGES) on October 10-12, followed by the biennial Genetic Analysis Workshop (GAW) on October 13-16.  I had the opportunity to participate in both conferences, and I… Read more »

Four New Add-on Scripts Available for Strand Flipping, Histogram Means, and Chi-Squared Calculation

The scripting environment in SVS 7 allows for cross-communication between the powerful Python scripting language and the tools used in data analysis. Scripting is often the most effective way to make new features available to customers prior to new software releases. We often write scripts based on a specific customer’s need and then expand availability to all customers, many who… Read more »

Best Practices for Incorporating Public Genotype Data in Your Study

The Golden Helix sales team recently came to me for recommendations regarding best practices for incorporating public controls in SNP GWAS.  It seems that there has been a surge of questions regarding this practice over the past few weeks from our customers.  Initially, I laughed at the irony of being asked to outline the best practices for what I see… Read more »

The What, Why, and How of Creating a Genome Map

Including the completion of the Human Genome Project in 2003, scientists have created whole genome sequence maps for over 1,000 species. From maize to oysters, the quest to investigate different species’ genetic code continues. Mapping is the “first step” that provides a baseline for further study into differences between species, the occurrence of certain diseases, and the prevalence of traits… Read more »

Increase Power and Data Quality with Advanced Genotyping and Imputation Methods

Accuracy and completeness of genotype data are among the most important factors for a successful genome-wide association study (GWAS), and must not be taken lightly.  The Golden Helix team is always on the lookout for methods to improve data quality, and we have recently found the BEAGLE and BEAGLECALL software packages to be very useful in this regard.  BEAGLE is… Read more »