Golden Helix Newsletter

 
GenomeBrowse 2.0

The added
value of GenomeBrowse

by Andreas Scherer, Ph.D., President and CEO

We released GenomeBrowse 2.0 earlier this year, allowing users to review all types of genomic data. Since then, it has received rave reviews from thousands of users around the world. Essentially, it's the Google Earth app for genomic data.

GenomeBrowse allows a user to sift through vast amounts of genomic data, and make it easy to focus on a single part or the whole. GenomeBrowse has reached global adoption; as of July 2014 thousands of users worldwide have begun to use this product. Continue reading »

The State of Variant Annotation: A Comparison of AnnoVar, snpEff, and VEP
by Andrew Jesaitis, Product Manager and Software Engineer

Different Ways
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 just how many assumptions went into the above statement. What transcript set are we using? In what part of the gene did the mutation occur? What subfeature of the gene are we looking at? Are there other ontologies for the variant? Why did we use the term we did?

In order to develop a tool to annotate variants, rules to answer all these questions have to be codified into software. Enumerating these assumptions means that a process that is subject to a great deal of human interpretation, is now a rigidly defined objective framework. There are currently three major tools that attempt to classify variants: Annovar, SnpEff and Variant Effect Predictor (VEP). It is no surprise that these tools do not always agree since the way the rules have been defined differ slightly between each application. Continue reading »

The Differences between EMMA and EMMAX
by Ashley Hintz, Field Application Scientist

I recently gave a webcast on GWAS in a model organism: Arabidopsis thaliana; a question was brought up about the differences between EMMA and EMMAX and why the results with each would differ.

Both of these algorithms are used in association studies to account for data sets that show population stratification and relatedness. However, there is a slight difference between how they are run. EMMA is compatible with datasets with a moderate to small n, but the computational power required for datasets with a large n is astronomical. Continue reading »
 
   Upcoming Webcast
Tips & Tricks for Genomic Analysis
AUG
6
  Wed, Aug 6th
12:00 pm EDT

In genomic research and analysis, there are common problems that many researchers run into.

In this webcast, Ashley Hintz, Field Application Scientist, will address some common topics that are fielded by our support team.

Webcast Registration



   Featured SVS Script
Consecutive Numeric Regression Analysis
Download » | Script repository »


   SNP-ITS
Population Structure & Genetic Improvement in Livestock
The genetic improvement of livestock has been a hot topic for almost a century, bringing together researchers, industry, and producers to work towards a common goal. Many countries currently employ extensive genetic selection programs in their cattle with pigs, sheep, and chicken close behind. View recording »


2014 Golden Helix Sumer School
We are incredibly excited to sponsor the 2014 Golden Helix Summer School (not directly affiliated with Golden Helix, Inc. (us)), hosted on the island of Aegina, Greece, from September 11th-15th, 2014. This year's theme is "Pharmacogenomics and Genomic Medicine: Bridging research and the clinic" Find out more »


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Recent Customer Success Highlights

PLoS ONE
Genome-Wide Delineation of Natural Variation for Pod Shatter Resistance in Brassica napus
Harsh Raman et al..
Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, Australia
Read the article »

Nature Immunology
The transcription factor IRF1 dictates the IL-21-dependent anticancer functions of TH9 cells
Frederique Vegran et al.
Universite de Bourgogne, Dijon, France
Read the article »


 
About Golden Helix
Golden Helix has been delivering industry leading bioinformatics solutions for the advancement of life science research and translational medicine for over 15 years. Our innovative technologies and analytic services empower scientists and healthcare professionals at all levels to derive meaning from the rapidly increasing volumes of genomic data produced from microarrays and next-generation sequencing. With our solutions, hundreds of the world's top pharmaceutical, biotech, and academic research organizations are able to harness the full potential of genomics to identify the cause of disease, improve the efficacy and safety of drugs, develop genomic diagnostics, and advance the quest for personalized medicine. Golden Helix products and services have been cited in over 800 peer-reviewed publications.

 



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