Guest Post: Stepping Outside My Open-Source Comfort Zone: A First Look at Golden Helix SVS

Bio_Stephen_Turner

I’m a huge supporter of the Free and Open Source Software movement. I’ve written more about R than anything else on my blog, all the code I post on my blog is free and open-source, and a while back I invited you to steal my blog under a cc-by-sa license.

Every now and then, however, something comes along that just might be worth paying for. As a director of a bioinformatics core with a very small staff, I spend a lot of time balancing costs like software licensing versus personnel/development time, so that I can continue to provide a fiscally sustainable high-quality service. Continue reading

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Greta Linse Peterson

How SVS Treats Gender in Calculating Genotype Statistics

non-autosomal

Recently several customers have asked how SNP & Variation Suite (SVS) treats gender when calculating genotype statistics. In this blog post, I will cover SVS’ current capabilities, what we have available through Python scripts, and what is coming in the near future. We thank all of our customers who have inquired about these capabilities and have given us valuable feedback for improvements. Continue reading

Posted in How to's and advanced workflows, Support | 1 Comment
Jared Bowden

Nature or Nurture: What Insight Can Science Provide?

bee

I recently transitioned jobs – from researching early diagnostics for Type II Diabetes using several omics technologies such as proteomics, metabolomics, and lipidomics – to working with genomics data at Golden Helix.  As scientists, one of the questions we face in examining  these many areas of data is differentiating between what Nature has provided us (in our genetic code) and what is the result of Nurture (environmentally-induced variations in the expression RNA, proteins, and metabolic signatures).

An example of this question in practice comes from one of my hobbies as an amateur apiarist (beekeeper).  The hive is predominantly a female-dominated world, and the functional purpose of each bee is the survival of the colony and support of the queen bee.  Amazingly though, despite the tens of thousands of female bees in a colony, typically only one of these females becomes the queen. Continue reading

Posted in General statistical genetics principles, Personal Genomics | Leave a comment
Jessica Vionas

Researcher Uses SVS for Pharmacogenetic Associations for 10 Years

Dr. Julia Pinsonneault

Dr. Julia Pinsonneault is a Research Scientist at The Ohio State University where she works to find biomarkers that guide effective treatment. Published recently in Neuropsychopharmacology, Julia has found success using SVS to find novel associations that move her research forward. Usually managing 3-5 research projects at a time from various cohorts, she found time in her busy schedule this month to chat for a few minutes about her experience with SVS. Continue reading

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Jessica Vionas

Analyzing PacBio Data with SNP & Variation Suite

As most in the Golden Helix community are aware, SNP & Variation Suite (SVS) can handle all sorts of data including files from Affymetrix, Illumina, Agilent, and Complete Genomics with its powerful data management capabilities. Announced in February, SVS is now part of the Pacific Biosciences Partner Program and has the ability to analyze PacBio files. Continue reading

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Christophe Lambert

Learning From Our GWAS Mistakes: From experimental design to scientific method

Learning From Our GWAS Mistakes

This month Biostatistics published online an open access article I co-authored with Dr. Laura Black from Montana State University: “Learning From Our GWAS Mistakes: From Experimental Design To Scientific Method.” The paper version is expected to come out in the April 2012 issue.

I’m hoping that you will take the time to read it. And I’m hoping you will violently agree or disagree with the contents of the article and post your thoughts to this blog.

This post extends on some of the themes of the paper, and continues my ongoing effort to examine the systems and paradigms in which we work and how we can improve or even replace them. I’m going to try to be more provocative here than the paper itself. It may insult you, but I’ll make sure to insult myself as well. Continue reading

Posted in Big picture | 6 Comments
Autumn Laughbaum

New Features in SVS: Accounting for Sex Chromosomes and Filter Columns by Variant Type

python

In the last couple of weeks, the SVS Script Repository has seen a handful of new additions.  This blog post highlights three new scripts, but as always, we welcome you to check out our repository regularly to enjoy the new and exciting functionality made possible by our Python integration in SVS!

(To get these, or any other scripts, simply go to the Golden Helix website, download the desired script, and save to the appropriate folder.  It will then be available for use in SVS.) Continue reading

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Jessica Vionas

Introducing SVS 7.6!

Compound Heterozygosity

It’s that time again! We here at Golden Helix are excited to announce SVS 7.6 with more features for DNA-Seq analysis, the addition of RNA-Seq functionality, reorganization of SVS into “packages” including two new ones, and the release of new plot types enabled by Matplotlib. It’s certainly been busy as we pack all this into the sixth installment of the most powerful collection of high-performance analytic tools for quickly identifying statistically significant genotype/phenotype associations and causal variants: SNP & Variation Suite. Continue reading

Posted in News, events, & announcements | 4 Comments
Bryce Christensen

Admixture and Blaine Bettinger

BlainBettinger

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 commentary on applications of genomic science for advancing personal and family history research.  I first learned about Blaine last May when he announced that he was committing his genomic data to the public domain and challenged any interested parties to analyze it and tell him what they learned.  As a scientist, he was aware of the limitations of the technology, but was curious to know if anybody might find something surprising.  As an intellectual property lawyer, he expressed interest in the question of whether it was even possible to truly commit one’s genomic data to the public domain.  (Anybody who attended ICHG/ASHG in Montreal may have heard some of the debate about whether genomic research data belongs to the researcher, the study subject, the funding agency, or some other entity.)  I immediately downloaded the data with grand visions of what I might do with it, but set it aside due to other obligations and forgot about it until rediscovering it just a few weeks ago. Continue reading

Posted in General statistical genetics principles, Personal Genomics | Leave a comment
Christophe Lambert

Never Let the Important Become Urgent: A reflection on the genetics supply chain and our need to increase value to the end patient

Never let the important become urgent

The turning of the calendar from 2011 to 2012 has been a good time for me to reflect on the lessons of the year and make resolutions for the new one. It is also the opportunity to step back and look at some of the larger systemic trends in our field and think about whether we are doing as much as we can with genetics to accelerate the delivery of healthcare solutions to the patient. I’d like to tie together several threads in this article. The first is to pay homage to a man who has done more for me than any other in understanding the nature of reality, Eli Goldratt. Drawing from his lessons on systems and supply chains, I’ll then make some observations about our field’s own genetics supply chain and the consequences of not producing enough value for the end patient. Further, as 2011 marks the 40th year of the war on cancer, Goldratt’s death by the same can lead us to pause and reflect on our own vulnerability to disease and spur us to not just redouble our efforts, but to ask ourselves what we might do systemically to accelerate the translation of innovations in genetics to the clinic. Continue reading

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