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VARIANT ANALYSIS

Quickly go from raw data to comprehensive variant analysis using an automated pipeline with integrated access to large variant databases. PRICING DOWNLOAD FREE TRIAL

Use Lasergene Genomics to accurately identify significant variants between multiple samples.

When you’re faced with a deluge of raw sequencing data, getting to the point of variant analysis can seem a long way off. Lasergene Genomics gets you there quicker, through an automated pipeline that assembles your reads to a template, performs variant calling, and then compares the variants across multiple samples, all without human intervention. Our variant calling tools have been proven to be more accurate than both our commercial and open source competitors, so you can rest easy in knowing that you can trust the results. Easily identify significant variants between multiple samples through a powerful filtering tools, rich graphical views, and integrated access to large variant databases, including Mastermind, dbSNP, GERP, dbNSFP, and the 1000 Genomes Project. Lasergene Genomics even makes it easy for you to compare and analyze multiple VCF files that come from other NGS software pipelines and annotate them with information from our custom genome template packages for enriched variant analysis.

Variant analysis in 4 simple steps

Variant Analysis Step 1

Step 1

Set up and run assembly

Variant Analysis Step 2

Step 2

Compare variants across multiple samples

Variant Analysis Step 3

Step 3

Filter to find variants of interest

Variant Analysis Step 4

Step 4

View variants within alignment

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Learn more about Variant Analysis

Resources | Tutorials | FAQs | Benchmarks | Citations | User Guide

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Resources

Please see our resources below for more information on variant analysis.

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DNASTAR’s SeqMan NGen vs. Four Alternative Pipelines: Variant Detection Comparison Using Illumina Data from NA12878

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SeqMan NGen vs. CLC Bio Genomics Workbench: Variant Detection Comparison Using Data from NA12878

Read White Paper

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SeqMan NGen vs. Two BWA+GATK Workflows: Variant Detection Comparison Using Illumina Data from NA12878

Read White Paper

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SeqMan NGen vs. Geneious: Variant Detection Comparison Using Data from NA12878

Read White Paper

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SeqMan NGen Assembly of Ion Torrent Exome Data With and Without Heterozygous Indel Removal: a Comparison Using NA12878 Reference Materials

Read White Paper

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Considerations for Next-Gen Sequence Assembly and Analysis Software Selection

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A Next-Gen Sequencing Software Workflow for Gene Panel Validation Control

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Automating Workflows in DNASTAR’s Lasergene Genomics Suite for High-Throughput Applications

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Identifying Candidate Variants and Their Effects on Protein Structure Starting from NGS Data or VCF Files

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Cloud Assemblies for NGS Sequences Webinar

Watch Webinar

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Variant Analysis in Lasergene Genomics

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Rapid, Large-Scale Prioritizing of Human Variants with Lasergene Genomics Suite

Read Blog Post

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How Much Disk Space Do I Need For My Templated Genome Assembly?

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Working with Variant Call Format Files in Lasergene Genomics

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Tutorials

Watch one of our videos or check out one of our written tutorials to learn more about variant analysis.

Exome Analysis Tutorial

See how to align exome resequencing data from all major NGS platforms against a reference sequence with unsurpassed ease and speed in Lasergene Genomics. Comprehensive post-assembly analysis options make it easy to identify and compare genetic variants as well as structural and non-coding variants. Advanced gene filtering offers the ability to determine the level of disruption to each gene caused by variations.

Visualizing Genes and SNPS from ArrayStar in GenVision Pro

This quick tip video demonstrates how to visualize groups of genes or SNPs from ArrayStar in GenVision Pro.

Sanger Validation for NGS Assemblies

If you are working with next-gen sequencing, you may wish to use Sanger sequencing data to validate the results of the assembly or variant calls. Lasergene Genomics supports this validation, allowing you to combine both data types into a single project in SeqMan NGen.

Multiple Genome Assembly and Variant Analysis

In this video, learn how to align next-gen sequencing data for multiple samples to a genomic reference then perform variant analysis for all samples.

FAQs

How long does it take to assemble and call variants?

This depends whether you are doing the assembly on your local computer or are using DNASTAR Cloud Assembly. Depending on hardware and depth of sequences, local whole-genome resequencing can take as little as 5 minutes for a bacterial assembly to 24+ hours for a mammalian genome. A typical whole exome sequencing assembly takes between 30 and 90 minutes. Regardless of workflow, cloud assemblies are much faster and multiple assemblies can also be run simultaneously.

How do I compare variants between multiple samples?

Multiple sample variant analysis is done in ArrayStar, part of Lasergene Genomics. Variant samples can be compared and filtered into sets of interest using customizable tables, a filter wizard, Venn diagram, heat map or scatter plot.

What supplemental variant data is available in the Variant Annotation Database?

For human resequencing data, DNASTAR provides access to the Variant Annotation Database, which contains variant information using coordinates from GRCh37 (hg19) and GRCh38. Annotations include information about the frequency of the variant in the general population, in specific populations, and in publications, as well as information concerning the variant’s impact on functionality. The annotation information comes from several sources, including:

  • Mastermind, the comprehensive database of genomic literature from Genomenon, providing access to NGS variant data from millions of PubMed publications.
  • 1000 Genomes Project and the Exome Sequencing Project (ESP)
  • dbNSFP v 4.1 which includes:
  • Functional impact predictions from Sorting Intolerant from Tolerant (SIFT), MutationTaster, and the Likelihood Ratio Test (LRT).
  • Evolutionary conservation scores from SiPhy, PhyloP, PhastCons and GERP++.
  • Pathogenicity and clinical significance impact from ClinVar.
  • Basic amino acid sequence information, Database of Single Nucleotide Polymorphism (dbSNP) IDs, and annotations from Uniprot and Interpro.

Can I import other annotation data into my variant analysis project?

Yes, you can import most any annotation data in text format, including gene and SNP level annotation data.

What types of variant analysis are available post-assembly?

Lasergene Genomics provides a wide variety of variant analysis tools, including:

  • Large-scale SNP comparisons across individuals and groups
  • Advanced gene filtering based on the level of disruption to each gene caused by variations
  • Comparison of groups of variants using text filters, tabular data, or graphical representations that include Venn diagrams, scatter plots and heat maps
  • The ability to send genes or variants of interest to SeqMan Ultra to view the read alignment at that position; or to GenVision Pro to view the assembly coverage for all samples simultaneously

Can Lasergene Genomics detect structural variations in genomic resequencing data?

Yes, Lasergene Genomics can detect copy number variation (CNV) and other structural variants as part of gene panel, whole exome and whole genome sequence analysis. Simply check the box for Calculate Copy Number Variation during assembly setup in SeqMan NGen. You can then view, filter and analyze CNVs and other structural variants using ArrayStar and SeqMan Pro.

Does Lasergene Genomics support BED or VCF files for targeted sequencing?

Yes. SeqMan NGen can read and utilize BED and VCF files in the assembly and can also create and export a VCF file during assembly. ArrayStar can export BED and VCF files.

Can I use VCF files created from another NGS software pipeline?

Yes, any VCF file in standard format is compatible. You will need to provide the same genome reference sequence (or genome version) along with the VCF files when you set up your variant analysis project in SeqMan NGen.

What advantages does DNASTAR provide for analyzing my VCF files?

We provide enriched variant analysis for VCF files including the ability to:

  1. Easily analyze and compare large number of variants across multiple samples.
  2. Comprehensively compare groups of variants using text filters, tabular data, or graphical representations that include Venn diagrams, scatter plots, and heat maps.
  3. Import additional database annotation/information that may be lacking in your VCF file. For example, most VCF files lack information regarding a variant’s effect on protein coding, but by providing the reference genome, SeqMan NGen will calculate synonymous and non-synonomous variants. We provide access to our custom Genome Template Packages (available for many organisms) and Variant Annotation Database (available for human only), which add additional useful annotations like dbSNP IDs, GERP scores, genotype and allele frequencies, evolutionary conservation, clinical significance, and more.
  4. Utilize a user-friendly interface for running the VCF file comparison and the analysis – no command line tools required.

Benchmarks

In most studies, especially when looking for rare mutations, having a reliable reference set with known variations isn’t feasible. To test the accuracy of NGS alignment and variant calling in Lasergene Genomics, we used SeqMan NGen to align whole human exome data from the Genome in a Bottle Consortium (GIAB) to the human genome. Because this is a well curated data set, we were able to compare the variant calls to the “answer” provided by GIAB. We also performed alignment and variant calling in several other software packages using the same data and comparable settings. We then looked at three metrics:

  1. Sensitivity – This is also known as the true positive rate, and is the ratio of correctly identified variants to the total known variants in the reference set. The higher the sensitivity, the greater the likelihood that a variant in the sample will be identified by the software.
  2. Specificity – Also known as the true negative rate, this is the ratio of non-variant calls to the total number of positions in the reference set that are known to be homozygous with the reference sequence. Specificity is inversely related to the number of false positives.
  3. False Discovery Rate (FDR) – This is the ratio of false positives to all variant calls made by the software. The FDR value for a variant caller allows you to understand how many variants in your project are likely to be false positives.

Because an accurate alignment is a necessary precursor to accurate variant detection, these metrics also help you understand the alignment accuracy from various software pipelines.

Results Summary:

Variant Analysis Accuracy Table
READ WHITE PAPER

Citations

Analysis of genome-wide variants through bulked segregant RNA sequencing reveals a major gene for resistance to Plasmodiophora brassicae in Brassica oleracea.
Dakouri, A., Zhang, X., Peng, G. et al. Sci Rep 8, 17657 (2018) doi:10.1038/s41598-018-36187-5.

Whole genome sequencing data for two individuals of Pakistani descent.
Khan, S., Kabir, F., M’Hamdi, O. et al. Sci Data 5, 180174 (2018) doi:10.1038/sdata.2018.174.

Novel variants in PAX6 gene caused congenital aniridia in two Chinese families.
Zhang, R., Linpeng, S., Wei, X. et al. Eye 31, 956–961 (2017) doi:10.1038/eye.2016.326.

Molecular characterization of Portuguese patients with dilated cardiomyopathy.
Sousa, Alexandra, et al. Portuguese Society of Cardiology, Volume 38, Issue 2, February 2019, Pages 129-139.

Detailed Characteristics of Tonsillar Tumors with Extrachromosomal or Integrated Form of Human Papillomavirus.
Pokrývková, B.; Saláková, M.; Šmahelová, J.; Vojtěchová, Z.; Novosadová, V.; Tachezy, R. Viruses 2020, 12, 42.

Expansion of phenotypic spectrum of MYO15A pathogenic variants to include postlingual onset of progressive partial deafness.
Chang, M.Y., Lee, C., Han, J.H. et al. BMC Med Genet 19, 29 (2018) doi:10.1186/s12881-018-0541-9.

A novel co-segregating DCTN1 splice site variant in a family with Bipolar Disorder may hold the key to understanding the etiology.
André Hallen, Arthur J.L. Cooper. bioRxiv 354100; doi: https://doi.org/10.1101/354100.

A mutation in the major autophagy gene, WIPI2, associated with global developmental abnormalities.
Musharraf Jelani, Hannah C. Dooley, Andrea Gubas, Hussein Sheikh Ali Mohamoud, Muhammad Tariq Masood Khan, Zahir Ali, Changsoo Kang, Fazal Rahim, Amin Jan, Nirmal Vadgama, Muhammad Ismail Khan, Jumana Yousuf Al-Aama, Asifullah Khan, Sharon A Tooze, Jamal Nasir. Brain, Volume 142, Issue 5, May 2019, Pages 1242–1254, https://doi.org/10.1093/brain/awz075.

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  • Easy and fast

    “It is easy and fast to identify SNPs, structural changes, and CNVs.”

    Kirk Nelson, Qpex Biopharma Inc.

  • A very powerful application

    “It is a very powerful application; A run can be assembled with a reference genome in few minutes. SeqMan NGen is one of the best software applications of DNASTAR.”

    Elisabeth Navarro, CNRS

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