This week, Dr. Jeffery Moore presented a webcast on the Molecular Sciences Made Personal. The webcast delved into Dr. Moore’s attempts to transform how they teach chemistry at the University of Illinois and demonstrated how he uses VarSeq with his students to examine exome data.
The following are the questions asked by the attendees. Please feel free to reach out to us at email@example.com if you have any other questions.
Question: How did you come about choosing Golden Helix over the other packages available?
Over the last year our blog has seen a boom in visits and of course, I became curious. What brings people to “Our 2 SNPs…”? So, I decided to take a look at the blog posts that our community find the most intriguing. Here are my findings:
- Comparing BEAGLE, IMPUTE2, and Minimac Imputation Methods for Accuracy, Computation Time, and Memory Usage - As the title hints at, this blog posts compares imputation methods. So which method takes the prize? All programs outperformed others in certain areas, so it really depends on your specific needs.
- Continue reading
In a previous blog post, I demonstrated using VarSeq to directly analyze the whole genomes of 17 supercentenarians. Since then, I have been working with the variant set from these long-lived genomes to prepare a public data track useful for annotation and filtering.
Well, we just published the track last week, and I’m excited to share some of the details involved in its making.
The track, named Supercentenarian 17 Variant Frequencies, GHI, provides not only the allelic frequency of observed variants in these 17 whole genomes, but also the counts of the heterozygous and homozygous genotypes for those individuals.
For example, when investigating a rare recessive disease, its probably safe to say any variant occurring in a homozygous state in a 110 year old individual is probably not your causal disease mutation.
So what was tricky about constructing this population variant catalog?
It turns out, quite a lot.
Last week we conducted a webcast on “Cancer Gene Panels”; you can find the recording here. We had some excellent questions which we answered during the webcast and a few more that we didn’t get to in the allotted time. Please find answers to those questions here:
1. Are Cancer Gene Panels just another stepping stone on the way to whole exome/genome analysis?
Cancer gene panels answer a very targeted question. Is this tumor mutated in a gene that has a known association to cancer AND do we have a treatment option for this particular mutation? If so, the clinician can continue the work of finalizing the diagnosis and putting a treatment plan together. If not, then we are dealing with a case that requires a more research oriented focus. Along the same lines, the usage of a panel approach minimizes the issue of incidental findings.
I am constantly on the lookout for fun or interesting datasets to analyze in SVS or VarSeq and recently came across a study looking into inherited cardiac conduction disease in an extended family (Lai et al. 2013). The researchers sequenced the exomes from five family members including three affected siblings and their unaffected mother and an unaffected child of one of the siblings. I’m going to take you through how I was able to analyze, annotate and filter this unique family structure in VarSeq.
The original dataset was downloaded from the European Nucleotide Archive: ENA Project PRJNA222575. The FASTQ files were aligned using BWA (Burrows-Wheeler Aligner) to generate BAM/BAI files, reads being 76bp paired-end. The five family members’ BAM files were given to GATK Unified Genotyper and variants were called across samples to recognize reference calls between samples that may be important for family variant analysis.
Several of our customers have published recently, using the SVS software and I wanted to share their work. Congrats to all!
It was a great trip down to Florida this year. AGBT 2015 was an exciting event with lots of great presentations. For us in this tightly-knit community it is an excellent networking opportunity to catch up with existing clients and partners, but also to make new connections.
Now, it is impossible to reflect on all the great talks. We were wowed by excellent research and the most recent findings. AGBT 2015 had four days full of premium research content. I am sure we all had our favorites. Here is a short list of talks that I found very entertaining:
Personal genome sequencing is rapidly changing the landscape of clinical genetics. With this development also comes a new set of challenges. For example, every sequenced exome presents the clinical geneticist with thousands of variants. The job at hand is to find out which one might be responsible for the person’s illness.
In order to reduce the search space, clinicians use various methods to filter out noise. Case-cohort analysis or sequencing additional family members can also improve diagnostic accuracy by eliminating variants that are present in non-carriers that are also present in the cases. There have been a vast amount of algorithms and filters developed for those scenarios.
This year’s abstract challenge was another great success. We received over 30 submissions and topics ranged from GWAS to RNA Seq to exome sequencing, and the list goes on. With so many excellent submissions this year, we chose 4 winners, with a tie for 3rd place.
Dr. Sergey Kornilov
Our first place winner is Dr. Sergey Kornilov, a Postdoctoral Associate in the Child Study Center at Yale University’s School of Medicine. Kornilov is part of the EGLab which performs research and clinical services focused on behavioral and molecular genetics. His submission focused on the genetic basis of developmental language disorder in a geographically isolated Russian-speaking population. Kornilov will present his work to the Golden Helix community in October and will receive a new Dell laptop as well as a free license of both SVS and VarSeq.
I spent a very eventful week at the Molecular TriCon in downtown San Francisco, and have been pondering the very clear trends that emerged by attending the clinical and NGS focused talks.
Cancer gene panels make sense economically and as “massively parallel” tests to inform therapy, but they are bound to get more complex.
Liquid biopsies of circulating tumor DNA (ctDNA) have the potential to impact how we conduct clinical trials, build early detection regiments and monitor for recurrence of cancer.
Clinical Exomes have excellent diagnosis yields, but whole genome sequencing provides a better exome and is close to price competitive.
The only constant is change: we all expect the FDA to say more about Laboratory Developed Tests (LDTs) and sequencing platform innovation to change the landscape for test developers.