If you’re a frequent visitor to our website or this blog, you’ll know we talk a lot about accuracy here. When it comes to your research, we understand that obtaining accurate and reliable results is paramount in deciding which software to use. So how accurate is our protein structure prediction program, NovaFold? And how can one test the accuracy of a protein model when the experimental structure is unknown? We can begin to answer these questions by looking at results from the Critical Assessment of Protein Structure Prediction (CASP) experiments.

Every two years, research groups around the world participate in the CASP competition to test their prediction tools against unpublished protein structures in a series of blind studies. The goal of these experiments, as stated on the CASP website, “is to obtain an in-depth and objective assessment of our current abilities and inabilities in the area of protein structure modeling.”

 
The I-TASSER algorithm, developed by Professor Yang Zhang at the University of Michigan and referred to as the Zhang-Server in the CASP competition, has taken first place in each of the past three competitions. This unique algorithm utilizes a combination of “threading” and “ab initio folding” to predict protein structure, resulting in highly accurate protein models, even in the absence of similar template structures. This is the same algorithm used by NovaFold, which can be accessed through Protean 3D, on our new cloud app, or on a Linux server.

Read our latest white paper to learn more about the CASP competition and how NovaFold utilizes I-TASSER to produce accurate protein models. Then, check out NovaFold on the Cloud to try a structure prediction for yourself. Academic and government users can predict their first structure free!

We’ve run the numbers and we are proud to announce that DNASTAR software continues to be the most widely cited sequence analysis software in peer-reviewed journals. To date, our software has been cited over 65,000 times. In 2016 alone, DNASTAR software was cited in over 4,000 publications! Last year, and every year since 1985, our software has been cited more than any of our commercial competitors.

We are proud to see our users’ work published month after month, and we are honored to be trusted by so many researchers around the world.  Check out the Publications section on our blog to see how others have used our software for different project types, from molecular biology to genome assembly, gene expression analysis to variant detection, and more.  And remember to cite DNASTAR in your own publications!

#10 Gibson Cloning

See how to perform virtual Gibson Cloning in Lasergene, one of the many new cloning methods introduced in Lasergene 14.

#9 Multiple Genome Assembly and Variant Analysis

Analyze variants for multiple genomes with our streamlined assembly and analysis tools, including our new Variant Annotation Database.

#8 Virtual Cloning Overview

Our redesigned cloning interface is now easier to use than ever before.

#7 De Novo Transcriptome Assembly and RNA-Seq Analysis for Non-Model Organisms Webinar

 Get an in-depth look at one of our most exciting new workflows!

#6 Predict a Protein Structure

 See how to go from sequence to structure in this 1-minute QuickTip video.

#5 Introducing Lasergene 14

See what’s new in our latest release!

#4 De Novo Transcriptome Assembly and Annotation

 Our new workflow for assembly and auto-annotation for any size transcriptome

#3 Variant Analysis Workflow

 Learn about our accurate, large-scale variant analysis tools, complete with integrated variant annotations

#2 De Novo Genome Assembly

Quickly and easily perform de novo genome assemblies using either long or short reads from all major next-gen sequencing platform

#1 RNA-Seq Analysis

The top new video of the year features our new, streamlined workflow for any RNA-Seq data set.

Lasergene Genomics Suite now includes access to the Variant Annotation Database (VAD) for human sequencing data. I recently spoke with DNASTAR Scientist, Dr. Tim Durfee about the VAD to get a better understanding of how the tool works and how it can help genomics and clinical researchers with their variant analysis.

Can you describe what the Variant Annotation Database is?

The VAD is a database resource that contains information on individual positions and alleles across the human genome. It is currently human genome specific. The major purpose of the VAD is to allow rapid prioritizing and ranking of the large number of variants found in any given sample relative to the reference genome. This can be on the order of thousands of variants for gene panels; tens of thousands for exomes; and millions for whole genomes. This kind of large-scale analysis is critical for the clinical sequencing market.

How can users access the information in the VAD?

Annotation information for each called variant in a specific sample is automatically retrieved from the VAD during project setup in ArrayStar. With the upcoming Lasergene 14.0 release, it will be added to the project directly following assembly and variant calling. The data is accessible in the ArrayStar SNP table and can be used to filter and create gene and SNP sets. For examples on how this can be done, take a look at our tutorial.

What is the source of the annotations in the VAD?

The data is from two major sources: the 1000 Genomes Project and dbNSFP (Database of Human Nonsynonymous SNPs and their Functional Predictions). As the name suggests, the dbNSFP data is on protein encoding positions in the genome. The data are organized into five broad categories:

1. Allele and genotype frequencies from the 1000 Genomes phase 3 data as well as from NHLBI’s Exome Sequencing Project. The 1000 Genomes data is available as global frequencies as well as frequencies for 26 populations grouped into 5 super populations. This data is extremely useful for filtering. For example, if you’re studying a rare disease that only occurs in a small number of individuals, you wouldn’t expect a relevant SNP to occur at high frequency in the population – typically, you filter for variants that occur less than 5% or even less than 1% in the population.

2. Functional impact prediction methods: LRT, MutationTaster, PolyPhen-2 (two models) and SIFT. The four methods use different strategies to predict whether a given non-synonymous change is deleterious to the function of the encoded protein.

3. Evolutionary conservation scoring systems: GERP++, SiPhy, PhyloP and PhastCons. These methods use sequence alignments of the human genome with the corresponding regions of other organisms to produce scores of how conserved each particular base is across evolution. In coding regions, the more evolutionarily conserved the particular base is, the more likely having that base in that position is important for the function of the encoded protein. Some methods (e.g. GERP++) can also be used to assess the importance of bases outside the coding regions.

4. Pathogenicity information from ClinVar: ClinVar is a central repository hosted by NCBI that catalogs and reviews human variation and its connection to disease.  The VAD uses the clinical significance field to allow filtering on different classifications including Benign and Pathogenic.

5. Miscellaneous information: The VAD also contains other types of information such as links to dbSNP Uniprot and Interpro that allow the user to easily retrieve additional data from those resources.

What are the advantages to using the VAD over a user’s own database or VCF file?

If a user has huge VCF files with the annotations, they would have to manually go through each position and retrieve the relevant information for that allele. With the VAD, all the annotations are automatically retrieved and readily available for filtering. The VCF is more useful as a record file of all the variants and their annotations that can be shared between applications.  For example, a VCF of alleles of interest produced by ArrayStar can be used by SeqMan NGen in subsequent assemblies to report on those positions.

How does this compare to other tools on the market today?

The major advantage of DNASTAR’s Variant Annotation Database is the seamless connection with the assembly and variant caller. With open source software, you have to first run the assembly, do the variant calling with a separate program, and then use yet another tool to add the annotation information. There is often a steep learning curve with each of these tools, which can make the overall process laborious. The DNASTAR pipeline integrates all these steps into one suite and allows for multiple sample comparison and filtering. Additionally, we provide the most accurate assembly and variant calling.

Want to learn more? Check out our variant analysis workflow page to see videos and benchmarks on NGS assembly and variant analysis in Lasergene Genomics Suite.

We are excited to announce the upcoming release of Lasergene 14, which will be available to download in the next several weeks. Check out our preview video to get a sneak peek at all the features in Lasergene 14, from enhanced cloning to genome visualization to protein docking, and much more!

Check out our newest video to see three different ways to find and compare genes and variants of interest for a variety of genomics and transcriptomics projects, including whole genome and exome assemblies, RNA-Seq and ChIP-Seq alignments, and more!

Whether you are working with NGS or Sanger data, whole genome sequencing or targeted resequencing, Lasergene provides highly accurate assembly and variant detection for every project. Check out these 10 recent publications citing Lasergene for variant analysis for genome and exome projects, and learn why our software is the most trusted, most accurate variant caller on the market.

In the latest installment of DNASTAR LabViews, we speak with Dr. Richard Buick of Fusion Antibodies to find out how his group uses NovaFold software as part of their antibody humanization service. Check out the interview below to learn more about antibody humanization, and hear what Fusion Antibodies customers have to say about the NovaFold structure prediction results!

Want to see more videos like this? Watch the full collection of customer interviews here on our blog, and contact us if you or someone in your lab would like to be featured in a future video!

This week, we’re sharing a video featuring one of our most popular workflows: Sanger sequence assembly and analysis in Lasergene Molecular Biology Suite. See how easy it is to assemble read data ­de novo or against a reference sequence, view the resulting alignment and SNPs, design sequencing primers, and annotate your results in our 2-minute video:

Want to see more videos like this? View our collection of customer interviews here.