The developers at Golden Helix have raised the bar again with the release of GenomeBrowe 2.0. About a year and a half after the initial release, Golden Helix has expanded the functionality of GenomeBrowse to fulfill feature requests from both fundamental research investigators and transitional scientists who require a visualization tool to gain key insight into their results.
The Golden Helix GenomeBrowse® tool features impeccable genomic data visualization, giving researchers the power to navigate their sequence data in a fluid and dynamic way. Pairing a high performance backend with a streamlined user interface has given way to a discovery process that is this year’s must have. And yes, GenomeBrowse 2.0 is still free! Continue reading
Science is a collaborative endeavor. Rarely is it in isolation that new discovery takes place. Unfortunately, using a computer to perform analysis is almost always a solitary activity. Sharing what you have found with members of your team often means squeezing around a small 13” glowing rectangle.
While looking at the same screen has its place, being able to save your findings and share them with a another person is enormously valuable. Even if the only person with whom you are sharing is yourself in 12 hours, decoupling time from analysis means that never again will someone be left wondering where that interesting variant was or what made it interesting in the first place.
We have wanted to integrate a way to “bookmark” into GenomeBrowse since it first launched. Many lunch-time conversations have centered around the best way to provide this functionality. Often GenomeBrowse is compared to a web browser. The idea of having a browser-like bookmark menu has a lot of appeal. But, unlike pages on the internet, a genomic region has no title, so seeing a list of Chr2:163,173,998 – 163,245,443, Chr4:53,499,919 – 54,278,649, etc does not help you remember why you bookmarked that region in the first place. Continue reading
As I write this article, Golden Helix has hundreds of clients in top research institutions world-wide. The adoption of our product at these institutions ranges from a few individual users to site licenses used by entire organizations. Because of the quality of SNP & Variation Suite (SVS) and GenomeBrowse, our competence in the field is recognized, and increasingly our clients reach out to us to help them with their general bioinformatics needs. For example:
- Clients – primarily pharma and biotech firms – outsource the bioinformatics portion of a study to our expert analysts.
- Many users of SVS or GenomeBrowse want to create a repeatable process, and we are asked to develop a custom implementation. This can be automated workflows or customized scripts to make the overall solution more tailored, seamless and efficient.
- Our users would like to receive custom training programs for their team or lab.
We recognize the need for a well-structured service offering that helps our clients make their day-to-day life easier and get even more value out of their investment in Golden Helix. For these reasons, we recently revamped and improved our services portfolio to better meet the needs of our clients. We offer the following services: Continue reading
New breakthroughs are being made every day in genomics. It’s a dynamic and fascinating industry, and with exceptional growth forecast in the DNA sequencing market, a new generation of people are entering the field: future researchers, clinicians, counselors and doctors. This new generation will need to learn not only the science, but also understand how to process the massive amounts of data generated with DNA sequencing (and genomics in general).
Managing large volumes of data is already a mission critical topic in bioinformatics, where many core facilities are overworked. They do their best to keep up with the demand, but going forward there will be more data, more projects and more people to support. How will bioinformatics keep up?
Now, as universities are putting educational programs together to prepare the next generation of scientists to understand the ins and outs of DNA analytics, they are running into obstacles. Bright kids who are fascinated by the science (human, animal, plant) are not necessarily computer programmers nor do they want to be. Yet, many of the tools used to teach basic analytic skills in genomics programs are public domain/open source programs that require enormous amounts of computer science knowledge to navigate. Continue reading
Today is a big day for us. Today we are announcing a major release of our flagship product, SNP & Variation Suite (SVS), to the general public. SVS 8 is a substantial improvement over the previous release in a number of dimensions (see detailed discussion on our What’s New page).
We’ve come a long way.
Over five years ago, in November 2008, we introduced SVS 7 as a powerful tool to conduct next-generation sequencing and GWAS studies. Since then, we have been adopted by hundreds of client organizations worldwide. SVS is being used by leading research organizations in the US, Canada, Latin America, Asia, Australia, Africa, and Europe.
About one and a half years ago, we launched the first version of our free, standalone genome browser. This tool was designed to help researchers view large sequencing files alongside public annotation databases in a fluid and intuitive way. Over 2,500 researchers in our field are using GenomeBrowse today. Continue reading
And the Winners Are…
We recently held our first ever research competition at Golden Helix – what a success! We received over 50 submissions from more than 20 different countries. And just as the countries varied, so did the research. Abstracts involved both DNA and RNA sequencing, GWAS (nope, it’s still not dead), and copy number variation. Subjects ranged from humans to wolves, cattle, alpaca, watermelon, and spinach, just to name a handful.
Yet, as excited as we were to get so many submissions, we were even more amazed by the quality of the abstracts. The research that is being done by those in the Golden Helix community is quite impressive, and needless to say, our judges had a very difficult time trying to pick just three winners from the applications. So, they picked six! That’s right, we chose two first place, two second place, and two third place winners, and we are giving away not one, but two free laptops, and ten free licenses of SVS!
And now, to announce the winners! (Drum roll please!)
Dr. Heather Huson
First place goes to both Dr. Heather Huson at Cornell University and John Eicher at Yale University. Huson’s research uses candidate gene and whole genome analysis to explore energy balance in dairy cattle as optimal energy balance is critical to yield and production. Eicher has conducted GWAS research that seeks to determine if an association exists between reading disability and language impairment in humans.
On my flight back from this year’s Molecular Tri-Conference in San Francisco, I couldn’t help but ruminate over the intriguing talks, engaging round table discussions, and fabulous dinners with fellow speakers. And I kept returning to the topic of how we aggregate, share, and update data in the interest of understanding our genomes.
Of course, there were many examples of each of these topics given by speakers and through the many conversations I had. The ENCODE project’s massive data output is illuminating the functional value of the genome outside protein coding genes. The CHARGE consortium, with its deeply phenotyped and heavily sequenced cohort of 14,000 individuals, will take a step forward in our understanding of the genome as large as those made by the HapMap and 1000 Genomes Project.
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 (and how NOT to), and data management and manipulation features in SNP & Variation Suite to more effectively utilize online databases. In this blog post, I’ll summarize his suggestions for how to use public data effectively.
It is common knowledge that there is a wealth of public data available to researchers: the NCBI, EGA, HapMap Project, 1000 Genomes Project, GAW, and more. Plus, there’s data that can be obtained from hardware vendors, software vendors such as Golden Helix, and even individual research labs who make data available on their websites. Continue reading
Weather.com currently says it feels like -24 degrees outside (yes, that’s negative) here in Bozeman, Montana. Which is why I’m more than a little jealous of Gabe Rudy and Andreas Scherer who get to go to San Francisco and Marco Island next week, respectively, where the weather is little more… well, let’s say… reasonable.
Andreas will be headed to Marco Island, Florida for AGBT this year on February 12-15. Consistently surveyed as one of the best general genomics meetings, AGBT features four packed days of networking and sessions on topics ranging from technology advancements to methodology development. If you’re going to AGBT this year, make sure to reach out to Andreas via LinkedIn or Twitter – he’d love the chance to meet.
And on the other side of the country, Gabe will be at Molecular Med Tri-Con 2014 from February 9-14 in San Francisco, California. This year Gabe has been invited to give a short course on NGS assembly and alignment as well as a session in the clinical sequencing portion called “Interpreting My DTC Exomes Using Public Access Clinical Databases” (details for both below). Those who have heard Gabe present know that both sessions are sure to be chock-full of insights and practical implementation techniques for sequence data. Make sure to carve out time to go to both! (And say “hi” to Gabe as well!)
See you there! Continue reading
The above screenshot shows the exomes of three species (Bison bison, Bos indicus, Bos taurus) aligned to the Bos taurus UMD 3.1 reference sequence.
In our recent webcast, Advancing Agrigenomic Discoveries with Sequencing and GWAS Research, Greta Linse Peterson featured bovine data which she download from the NCBI website. The data was downloaded in SRA format and in order to analyze the data in SVS, the files had to be converted to BAMs and then merged into a single VCF file. Since many of you are accustomed to wrangling your data on a regular basis (or maybe you leave the wrangling to someone else), we thought we would share the secondary analysis steps we used when preparing the data. Our goal was to run the data through a common, “plain vanilla” pipeline, so that we were not relying on any special features during our downstream analysis. As such, we chose to use a combination of BWA and GATK; common tools that are often used in conjunction with each other. Continue reading