Dr. Laura Li and her colleagues at the Children’s Hospital Los Angeles (CHLA) are working to determine the underlying genetic causes of Optic Nerve Hypoplasia (ONH), which is still unclear. ONH is the absence or under-development of the optic nerve and is currently the leading ocular cause of vision impairments and blindness in young children. ONH can also be combined… Read more »
December’s webcast will provide the Golden Helix community with a more in-depth look at CNV analysis in VarSeq. On December 7th, Dr. Nathan Fortier will discuss the challenges and metrics surrounding CNV detection and then demonstrate VarSeq’s new capability from VCF to clinical report. Wednesday, December 7th @ 12:00 PM, EST Numerous studies have documented the role of Copy Number Variations (CNVs)… Read more »
True to its nature, VarSeq offers multiple data export options. You can export result tables from VarSeq to Text, VCF, a VarSeq annotation file and most importantly an XLSX (Excel) File. VarSeq’s Excel export options provide a lot of flexibility in the information that is exported and preserve the formatting of data during the export process from VarSeq to Excel. This… Read more »
While clinical assessments of germline mutations have been collected in ClinVar under the stewardship of the NCBI and the collaborate effort of many testing labs, the same type of resource has been missing for mutations that could informal clinical care in Cancer. Or at least, that is what I thought until I started to work with CIViC. With the stewardship of… Read more »
One of the tools at the top of the toolbox for researchers working with microarray data is genotype imputation. Genotype imputation is the process of inferring the genotype of one or more markers based on the correlation pattern (aka linkage disequilibrium or LD) of the surrounding markers for which genotypes are known. We have now integrated a natively ported version of BEAGLE into Golden… Read more »
This month’s webcast, Agrigenomics 2.0 – Advanced Analysis to Accelerate Discovery, will feature two well known Agrigenomic researchers and long-time Golden Helix customers, Christopher Seabury of Texas A&M and Holly Neiburgs of Washington State University. These two will join our own Gabe Rudy for a look at advanced workflows in SVS to advance mammalian genetic research. We hope you can join us! Wednesday,… Read more »
The new Annotate and Filter algorithm is now available with the release of SVS 8.6.0, see the release notes for full details on all new and updated features. To access this new functionality, you simply need to update your SVS installation to the new version. The update can be done by clicking the Update Available link at the bottom of… Read more »
Dr. Sergey Kornilov, a Duncan Scholar in Molecular and Human Genetics at Baylor College of Medicine, combines his broad psychology background with genetics to research the genetic basis of neurodevelopmental disorders with a unique dual perspective. Neuro-developmental disorders, for example, those of the spoken and written language, affect many worldwide – up to 10% of preschool children. In most cases, these… Read more »
It’s hard to believe that summer has already faded into fall and that ASHG 2016 is right around the corner! 2016 has been quite a busy year for us so far at Golden Helix. We have been working hard to bring our community the very best tools available for variant interpretation and SNP analysis. This year at ASHG, you can… Read more »
Copy Number Variants have been important to clinical genetics for quite a while now. So, what has made now the right time to be looking at calling CNVs from NGS data? Well, there are a number of good reasons. The dominant one is simply that the NGS data you are already creating for calling variants can be used in many cases… Read more »
Copy Number Variations (CNVs) play an important role in human health and disease, and the detection of CNVs in clinical samples has the potential to improve clinical diagnoses and inform treatment decisions. Yet until now, if you wanted to have CNVs on your targeted gene samples, you would need an alternative assay such as Chromosomal Microarrays (CMAs). In this webcast,… Read more »
Gabe Rudy’s webcast yesterday, Big Data at Golden Helix: Scaling to Meet the Demand of Clinical and Research Genomics, was a huge success with well over 300 registered. In today’s blog post, I wanted to recap the Q&A session with Gabe. If you missed the webcast, check it out! Question: What is the end goal for an application like Warehouse? Answer: The… Read more »
Any validated bioinformatics pipeline must be continuously monitored. Quality management in clinical testing labs ensures that any divergence from predefined quality metrics during the analysis of clinical samples is investigated. For example: There is an insufficient number of sequence reads that passed the predefined base quality score threshold The number of variants identified in a data set may deviate substantially… Read more »
Big data is here, but fear not, you don’t need a Hadoop cluster to analyze your genomes or your cohorts of tens of thousands of samples! It turns out, for the kind of algorithms employed in variant annotation and filtering, running optimized local programs is often faster anyway. As we support our diverse customer base, we have definitely seen the… Read more »
Pruning your data based on Linkage Disequilibrium (LD) values is an important quality assurance step for GWAS analysis. In particular, some tests such as Identity by Descent Estimation (IBD), Inbreeding Coefficient Estimation (f) and Principal Component Analysis (PCA) will obtain better results if the markers used are not in linkage disequilibrium with each other. Therefore, Golden Helix’s SVS provides the… Read more »
Wednesday, September 21st @ 12:00 pm EDT Every day, the trove of genomic data is growing. Clinics are sequencing targeted genes at high read depths to report out genetic tests. Research groups are adding new exomes and genomes to their disease-specific cohorts. Agricultural breeders are genotyping their herds and flocks by the thousands of thousands. The conventional attitude to big… Read more »
After the Wet Lab process has been completed, the bioinformatics analysis of the sequencing data work begins. The next three blogs will focus on three aspects of this process. The building blocks of a bioinformatics pipeline, documentation and validation (today’s topic) Quality Management Clinical Reporting The Building Blocks of an NGS PipelineThe bioinformatics process to analyze NGS data occurs in three… Read more »
Getting the NGS wet bench process right is not a small undertaking. Targeted NGS assays such as multigene panels or exome sequencing allow for the targeted analysis of genomic regions that are of particular interest. For every sample type, e.g. blood, formalin-fixed paraffin-embedded specimens, saliva etc, there must be a detailed protocol in place outlining how each sample type is going… Read more »
We have come a long way since Next-Generation Sequencing (NGS) evolved as a set of technologies in the 1970s. The higher throughput and rapid reduction of costs associated with NGS have lead to the accelerated adoption of clinical testing that we are experiencing today. Currently, it is applied to analyze inherited diseases, tumors, hematologic malignancies and infectious diseases. It is… Read more »
Join us for a guest presentation Personalized Medicine through Tumor Sequencing by Dr. Jeffrey Rosenfeld! Wednesday, September 7th 12:00 pm EDT The identification of medications that target specific gene mutations is one of the major recent advances in cancer therapy. In 2001 Gleevec was approved to treat patients with the BCR-ABL fusion in chronic myelogenous leukemia (CML). Since then many more drugs… Read more »
