Category Archives: Best practices in genetic analysis

Unique Labs, Common Tool: Making VarSeq Ready for Clinical Workflows

         April 9, 2015

As VarSeq has been evaluated and chosen by more and more clinical labs, I have come to respect how unique each lab’s analytical use cases are. Different labs may specialize in cancer therapy management, specific hereditary disorders, focused gene panels or whole exomes. Some may expect to spend just minutes validating the analytics and the presence or absence of well-characterized… Read more »

Introducing Phenotype Gene Ranking in VarSeq

         March 3, 2015

Personal genome sequencing is rapidly changing the landscape of clinical genetics. With this development also comes a new set of challenges. For example, every sequenced exome presents the clinical geneticist with thousands of variants. The job at hand is to find out which one might be responsible for the person’s illness. In order to reduce the search space, clinicians use various methods… Read more »

Q&A from our December Genomic Prediction webcast

         February 12, 2015

Our Genomic Prediction webcast in December discussed using Bayes-C pi and Genomic Best Linear Unbiased Predictors (GBLUP) to predict phenotypic traits from genotypes in order to identify the plants or animals with the best breeding potential for desirable traits. The webcast generated a lot of good questions as our webcasts generally do. I decided to begin to share these Q&A… Read more »

To Impute, or not to Impute

         February 5, 2015

Genotype imputation is a statistical technique for estimating sample genotypes at loci that were not directly assayed by sequencing or microarray experiments.  There are several reasons why you might want to use imputation in a research study.  For example: These are all important applications for imputation technology and can make significant contributions to a successful study.  There is also a… Read more »

Genetic Testing for Cancer

         January 20, 2015

In 1914 the German cytologist Theodor Boveri coined the phrase “Cancer is a disease of the genome”. At this time his ideas were equally revolutionary as they were highly contested. Fast forward. More than hundred years later, Next-Generation Sequencing effectively permits a highly sensitive analysis of cancer cells. It can help us to understand mutations associated with cancer development and… Read more »

Dr. Andreas Scherer to speak at ITI 2015

         January 15, 2015

The Integrative Therapies Institute is soon hosting the annual, ITI 2015 conference January 23rd through the 25th in sunny San Diego and our own Dr. Andreas Scherer has been invited to speak. Some of the most prominent genomic and integrative medicine specialists will gather at ITI 2015 to share case studies and protocols with the community. Attendees can expect to… Read more »

Analyzing Whole Exome, Large-n Cohorts in SVS

         November 25, 2014

It’s come to my attention in recent weeks, through various customer interactions, that many are not aware of the fantastic functionalities that exist in SNP and Variation Suite (SVS) for large-n DNASeq workflows; this includes large cohort analyses with case/control variables. The data you’ll see below is the publically available 1kG Phase 1 v3 Exome sequences from 1,092 individuals with… Read more »

New Plugin for Ion Torrent Server

         October 21, 2014

Golden Helix is proud to announce the release of the Golden Helix GenomeBrowse Plugin for Ion Torrent server. The new plug-in enables adding selected BAM files from Torrent Server reports directly into GenomeBrowse. The BAM files remain on the torrent server and are streamed from the server on demand using your credentials. This feature allows GenomeBrowse users to visualize genomic… Read more »

Variant Notation: In simplicity we find complexity

         October 9, 2014

Recently, I have been thinking a lot about Human Genome Variation Society (HGVS) notation — you know “G dot”, “P dot”, and “C dot”. HGVS has quickly become one of the most common ways to represent variants.  It’s no wonder that HGVS nomenclature is used so widely. It provides an easily readable, compact representation of a variant. Since it is… Read more »

Top 3 Most Viewed Tutorials from Golden Helix

         September 12, 2014

Tutorials are ever-present in the world today, and for good reason. Why struggle through a complicated process yourself, when there is already a guide established to assist? While no one would suggest that a tutorial is the only way to complete a project, it is certainly a nice starting point. This rings true with genetic software as well. There are… Read more »

Leveraging SVS for NGS Workflows

         August 19, 2014

Over the last decade, DNA sequencing has made vast technological improvements. With the cost of sequencing decreasing significantly, sequencing technology has become a product for the masses. The sequencing technology and programs that were once used exclusively by major research institutions are now becoming available in many research facilities around the globe. These tools produce large amounts of data sets… Read more »

RefSeq Genes: Updated to NCBI Provided Alignments and Why You Care

         August 14, 2014

You probably haven’t spent much time thinking about how we represent genes in a genomic reference sequence context. And by genes, I really mean transcripts since genes are just a collection of transcripts that produce the same product. But in fact, there is more complexity here than you ever really wanted to know about. Andrew Jesaitis covered some of this… Read more »

Runs of Homozygosity Updated

         August 12, 2014

For the SVS 8.2 release we decided to improve upon the existing ROH feature. The improvements include new parameters to define a run and a new clustering algorithm to aide in finding more stringent clusters of runs. The improvements were motivated by customer comments and a recent research paper by Zhang 2013, “cgaTOH: Extended Approach for Identifying Tracts of Homozygosity,”… Read more »

Have you ever had a bad experience with a VCF file?

         August 5, 2014

“Who has ever had a bad experience with a VCF file?” I like to ask that question to the audience when I present data analysis workshops for Golden Helix. The question invariably draws laughter as many people raise their hands in the affirmative. It seems that just about everybody who has ever worked VCF files has encountered some sort of… Read more »

The State of Variant Annotation: A Comparison of AnnoVar, snpEff and VEP

         June 25, 2014

Up until a few weeks ago, I thought variant classification was basically a solved problem. I mean, how hard can it be? We look at variants all the time and say things like, “Well that one is probably not too detrimental since it’s a 3 base insertion, but this frameshift is worth looking into.” What we fail to recognize is… Read more »

Public Data? What’s that good for anyway?

         February 12, 2014

Dr. Bryce Christensen recently gave a webcast on Maximizing Public Data Sources for Sequencing and GWAS Studies in which he covered options for getting GWAS and sequence information online, tips for working with these datasets and what you’ll see in terms of data quality and usefulness, how to use public data sources in conjunction with your GWAS or sequence study… Read more »

Guest Post: Finding Rare Pieces of Hay in a Haystack

         August 19, 2013

Utilizing Identical Twins Discordant for Schizophrenia to Uncover de novo Mutations We are living in exciting times – the reality of high-resolution Cand individual genome sequencing now offers renewed hope in the search for the causes of complex diseases. When this technology is combined with genetic relationships, individual sequences add unrivaled proficiency. Our lab is located in London, Ontario, Canada… Read more »

Population Structure + Genetic Background + Environment = Mixed Model

         March 22, 2013

A few months ago, our CEO, Christophe Lambert, directed me toward an interesting commentary published in Nature Reviews Genetics by authors Bjarni J. Vilhjalmsson and Magnus Nordborg.  Population structure is frequently cited as a major source of confounding in GWAS, but the authors of the article suggest that the problems often blamed on population structure actually result from the environment… Read more »

Follow Along on an Analyst’s Journey to Filter Whole Genome Data to Four Candidate Variants in SVS

         March 14, 2013

Last week Khanh-Nhat Tran-Viet, Manager/Research Analyst II at Duke University, presented the webcast: Insights: Identification of Candidate Variants using Exome Data in Ophthalmic Genetics. (That link has the recording if you are interested in viewing.) In it, Khanh-Nhat highlighted tools available in SVS that might be under used or were recently updated. These tools were used in his last three… Read more »