Author Archives: Bryce Christensen

Bryce Christensen

About Bryce Christensen

Dr. Bryce Christensen fills two roles at Golden Helix as he is both the Director of Services as well as a Statistical Geneticist. Bryce joined GHI in 2009 from the University of Utah where he earned his PhD in Genetic Epidemiology and Biomedical Informatics. Before undertaking his graduate studies, Bryce worked for 2 years as a data analyst at Mayo Clinic in the Division of Biostatistics. Outside of work, Bryce has an affinity for restoring motorcycles and is currently in search of his next restoration project.

A few thoughts from IGES

Late last month I had the opportunity to attend one of my favorite events: the annual meeting of the International Genetic Epidemiology Society (IGES).  This year’s conference was held in Vienna, in conjunction with the Genetic Analysis Workshop (GAW) and … Continue reading

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

“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 … Continue reading

Posted in Best practices in genetic analysis, Bioinformatic support, Customer Questions | Tagged , , , | 3 Comments

“Intriguing Findings Are for Romance Novels”

A report from the World Congress of Psychiatric Genetics Earlier this month, while much of the genetics community was scrambling to edit and print their posters for ASHG, I had the opportunity to attend WCPG, the World Congress of Psychiatric … Continue reading

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Population Structure + Genetic Background + Environment = Mixed Model

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, … Continue reading

Posted in Best practices in genetic analysis, General statistical genetics principles, Plant & animal | 3 Comments

Election Season: Which Exome Chip Wins?

It has now been about a year since Illumina and Affymetrix announced their respective exome genotyping arrays.  Both products were launched with ambitious visions of how they would enable researchers to learn significantly more about the cause of human diseases. … Continue reading

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Why You Should Care About Segmental Duplications

My work in the GHI analytical services department gives me the opportunity to handle data from a variety of sources.  I have learned over time that every genotyping platform has its own personality.  Every time we get data from a … Continue reading

Posted in Best practices in genetic analysis, How to's and advanced workflows | 2 Comments

Admixture and Blaine Bettinger

Allow me to introduce you to Blaine Bettinger.  Blaine is a patent attorney who holds a PhD in Biochemistry with a concentration in genetics.  He is also a family history enthusiast who writes the Genetic Genealogist blog, where he gives … Continue reading

Posted in General statistical genetics principles, Personal genomics | 2 Comments

Sequence Analysis Methods Not Just for Sequence Data

Speaking as somebody with a long history in data analysis, there are few things I find more exciting and tantalizing than new analysis methods that might apply to a problem I am trying to solve or was unable to solve … Continue reading

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Going Coast to Coast for the Latest NGS News

Last week I was able to attend two very interesting conferences about the latest developments in the analysis of sequence data.  I started the week in San Diego at the Illumina iDEA Conference and finished it in Philadelphia at Children’s … Continue reading

Posted in News, events, & announcements | 1 Comment

Updates to CNAM Make SVS the Fastest and Most Accurate Copy Number Tool for Common and Rare CNVs

A recent email from a user of SVS: “Your CNAM Optimal Segmentation algorithm is by far the best I ever used and believe me, I’ve tried many. Great use of the GPU for segmentation – it is 3x faster than … Continue reading

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