Congratulations to all of our customers who have recently published! It’s always a pleasure to see the interesting and useful work conducted in part with the aid of our software, and we hope you enjoy reading about it as well.
I was definitely an early adopter when it comes to personal genomics. In a recent email to their customer base announcing their one millionth customer, they revealed that I was customer #44,299.
And I have been consistently impressed with the product 23andMe provides through their web interface to make your hundreds of thousands of genotyped SNPs accessible and useful.
It takes an impressive amount of data science and statistical genetics to provide the trait and risk profiles they do. They also clearly take an engaged and caring stance on the ethics and risks of providing this data to users.
Today, we are proud to announce our collaboration with Fulgent Diagnostics, a CLIA certified molecular diagnostics lab. Fulgent offers more than 4,000 single gene tests among others and will implement VSPipeline to help speed up their analysis and interpretation process. On our quest to enable precision medicine, we look forward to working with Fulgent and other diagnostics labs in the near future. Please see the full press release here.
VarSeq now supports analysis of paired Tumor/Normal samples! Tumor/Normal support has been one of the most common feature requests for VarSeq since it was launched late last year, and we are excited to make this functionality available to all of our VarSeq users in the latest update (version 1.1.4).
VarSeq is a powerful platform for annotation and filtering of DNA sequence variants from many different study designs. It can handle data of any scale, from targeted sequencing to whole exomes and whole genomes. The new Tumor/Normal support creates a specific mode for handling paired samples. In this mode, the basic analysis unit is not one sample, but a pair of samples. Data filters can be created with decision rules specific to either the tumor or normal specimen, and those filters can then be saved as a workflow template that can be applied to large batches of samples in the future.
Recently, Golden Helix, Inc. announced the addition of VSPipeline to our VarSeq software suite. VSPipeline is a command-line interface that will allow high throughput environments the ability to tap the full power of VarSeq’s algorithms and flexible project template system from any command line context, including existing bioinformatics pipeline.
So, what is the big deal?
Here are the top five most important aspects of this new product.
1. Repeatable Workflows: For our users in CLIA and CAP certified labs, it’s a convenient way to lock down a workflow that has been designed in VarSeq. Once this task has been accomplished, this workflow (e.g. a gene panel or a specific whole exome workflow) can be automated. This further the reduces the chance of any human error.
Recently, customer Xin Geng of Auburn University published a paper using SVS, and we wanted to share his story with you. Please feel free to contact us if you have questions or if you would like to learn more about SVS at email@example.com.
For PhD graduate student Xin Geng, conducting Genome Wide Association Study (GWAS) to uncover the quantitative trait loci (QTL) controlling disease resistance in catfish was not just an interesting study, but potentially the start of finding a way to improve the economics of the aquaculture industry in the United Sates and China.
One of the lesser known functions in SVS allows the user to create Venn diagrams comparing variants found in multiple spreadsheets. These different spreadsheets could come from individuals samples, a case vs. control group or several variant databases. It is a helpful tool for visually comparing different variants.
Start by creating spreadsheets for each group/samples you’d like to compare. The first example here is for a rare variant case/control study. The whole dataset is split into two spreadsheets, one for cases and another controls. This can be easily accomplished by right-clicking on the C/C column and selecting Activate by Category, then choose one category and click OK. The other group will turn gray and become inactive. Now you can do a row subset and have a new spreadsheet. You can repeat the process for the other group(s).
A few months ago in Golden Helix’s 2nd Annual Abstract Challenge, Dr Raluca Mateescu tied for third place with her entry on the palatability of beef. We mentioned in our previous post highlighting all of the challenge winners that Dr. Mateescu would be presenting her work for the Golden Helix community and the time has come! Next week for our monthly webinar, Wednesday July 8th, Raluca will present “Genomic Analyses on the Palatability of Beef”. (Want to join? Register here.) As a preface to the webcast, we wanted to provide you with a short introduction to Dr. Mateescu and her research goals.
As an Associate Professor in the Department of Animal Sciences at the University of Florida, Dr. Mateescu’s research is focused on the biological traits of beef cattle, sheep and goat molecular genetics. Her over-arching goal is to unravel the genetic basis for the phenotypic variability in biological traits of economic importance that have a complex inheritance. But what does that really mean?
This last week I had the pleasure of attending the fourth annual Clinical Genome Conference (TCGC) in Japantown, San Francisco and kicking off the conference by teaching a short course on Personal Genomics Variant Analysis and Interpretation.
Some highlights of the conference from my perspective:
- Talking about clinical genomics is no longer a wonder-fest of individual case studies, but a pragmatic discussion of standards, data sharing and using the right tools for the right job.
- Early detection, prevention, and understanding wellness versus disease states can leverage genomics but also involves longitudinal measurements and many human factors.
- Some cancer types, such as non-small cell carcinomas clearly benefit from integrative analytics of multiple assays (WGS, mate-pair seq for SVs/CNVs, PCR for expression), but the complexity and cost is high. In other words, after the relative simply clinical assays of onco-gene panels to suggest targeted molecular therapies, it gets hard fast!