Category Archives: General statistical genetics principles

Our top eBooks for genomics enthusiasts

genomics ebooks

Our eBook series is made-up of short reads that cover a range of genomic industry topics. From simple bioinformatic concepts to the detailed structure of a genetic data warehouse, we have committed ourselves to provide the community with premium educational resources – at no cost! The series is constantly changing with revisions and new additions, but we’ve found our top… Read more »

Revisiting the Five Splice Site Algorithms used in Clinical Genetics

Interpretation of variants in accordance with the ACMG guidelines requires that variants near canonical splice boundaries be evaluated for their potential to disrupt gene splicing [1]. The five most common tools for splice site detection are NNSplice, MaxEntScan, GeneSplicer, HumanSplicingFinder, and SpliceSiteFinder-like. Because these algorithms have been made easily accessible in the bioinformatics tool Alamut, they have been canonized for… Read more »

Top 10 Posts for Understanding Clinical Annotation of Genomic Variants

Top 10

The VarSeq clinical platform is built on a strong foundation of data curation and annotation algorithms to ensure the variants identified have all the information required to make the correct clinical assessments.  It’s easy to make light of “variant annotation”, but the details run very deep into the roots of how we represent genomic data, how public data is aggregated, stored… Read more »

SVS, Population Genetics, and 1000 Genomes Phase 3

One frequent question I hear from SVS customers is whether whole exome sequence data can be used for principal components analysis (PCA) and other applications in population genetics. The answer is, “yes, but you need to be cautious.” What does cautious mean? Let’s take a look at the 1000 Genomes project for some examples.

Genomic Prediction and How it’s Used

Golden Helix is excited to host a webinar on Tuesday August 26th discussing the Genomic Prediction methods which were recently integrated into the SVS software. Genomic prediction uses several pieces of information when calculating its results. Genetic information is used to predict the phenotype or trait for the individuals. The phenotypic trait data can be provided for a subset or for all… Read more »