Tag Archives: Golden Helix

All I Want for Christmas Is a New File Format for Genomics

Tis the season of quiet, productive hours. I’ve been spending a lot of mine thinking about file formats. Actually, I’ve been spending mine implementing a new one, but more on that later. File formats are amazingly important in big data science. In genomics, it is hard not to be awed by how successful the BAM file format is. I thought… Read more »

Comparing BEAGLE, IMPUTE2, and Minimac Imputation Methods for Accuracy, Computation Time, and Memory Usage

Genotype imputation is a common and useful practice that allows GWAS researchers to analyze untyped SNPs without the cost of genotyping millions of additional SNPs. In the Services Department at Golden Helix, we often perform imputation on client data, and we have our own software preferences for a variety of reasons. However, other imputation software packages have their own advantages… Read more »

More Mixed Model Methods!

      Golden Helix    June 6, 2013    4 Comments on More Mixed Model Methods!

Thanks to everyone for the great webcast yesterday. We had over 850 people register for the event and actually broke the record! Take that Bryce and Gabe! If you would like to see the recording, view it at: Mixed Models: How to Effectively Account for Inbreeding and Population Structure in GWAS. While preparing for this webcast, we chose to focus… Read more »

The Murky Waters of Variant Nomenclature – You Could Be Missing Vital Information

When researchers realized they needed a way to report genetic variants in scientific literature using a consistent format, the Human Genome Variation Society (HGVS) mutation nomenclature was developed and quickly became the standard method for describing sequence variations. Increasingly, HGVS nomenclature is being used to describe variants in genetic variant databases as well. There are some practical issues that researchers… Read more »

The State of NGS Variant Calling: DON’T PANIC!!

I’m a believer in the signal. Whole genomes and exomes have lots of signal. Man, is it cool to look at a pile-up and see a mutation as clear as day that you arrived at after filtering through hundreds of thousands or even millions of candidates. When these signals sit right in the genomic “sweet spot” of mappable regions with… Read more »