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What is VarSeq?

VarSeq is an intuitive and effective software solution tailored for performing variant analysis on gene panels, exomes, and entire genomes. This all-encompassing platform simplifies third-party analysis, enabling users to seamlessly automate their processes and scrutinize variants within diverse genomic frameworks. With VarSeq, researchers can tackle the intricacies of genomic data more easily, facilitating a straightforward navigation and understanding of their findings. The application includes a powerful filtering and annotation system that allows for the efficient management of large variant datasets. By utilizing a series of filters, users can quickly narrow down their variant lists to focus on the most pertinent findings. After defining suitable parameters for their analyses, VarSeq enables users to save their filter settings, which makes it possible to apply the same analytical method across various datasets. This automated process is particularly beneficial in high-throughput environments, as it can be consistently executed on multiple batches of samples. Furthermore, the software's real-time filtering features allow researchers to rapidly adjust and refine their analysis workflows based on specific requirements, thereby enhancing the overall research process. Consequently, VarSeq plays a pivotal role in significantly simplifying the variant analysis journey for genetic research, making it an indispensable tool for researchers in the field.

What is Evo Designer?

Evo Designer, an innovative instrument developed by the Arc Institute, leverages the capabilities of the Evo 2 genomic foundation model to assist in both the creation and examination of DNA sequences. By allowing users to input nucleotide sequences or choose particular organisms, the platform generates tailored DNA sequences that meet specific research requirements. Moreover, it provides comprehensive annotations for coding regions and enables 3D visualizations of prokaryotic protein structures through ESMFold, thereby deepening users' comprehension of protein architecture. Additionally, Evo Designer assesses the complexity of sequences by calculating perplexity and per-nucleotide entropy, offering researchers insights into the variability of their data. Central to this tool is the Evo 2 model, which has been trained on a vast dataset exceeding 9 trillion nucleotides from a diverse range of prokaryotic and eukaryotic genomes. Harnessing an advanced deep learning framework, this model accurately represents biological sequences at a single-nucleotide level and can accommodate a context window of up to 1 million tokens, ensuring meticulous sequence analysis. The diverse features offered by Evo Designer significantly enhance genetic research, making it a crucial asset for scientists in the field. As a result, the tool not only streamlines the process of DNA sequence analysis but also fosters deeper insights into genetic structures and their functions.

Media

Media

Integrations Supported

Evo 2
GenomeBrowse
VSClinical

Integrations Supported

Evo 2
GenomeBrowse
VSClinical

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Golden Helix

Date Founded

1998

Company Location

United States

Company Website

www.goldenhelix.com/products/VarSeq/

Company Facts

Organization Name

Arc Institute

Company Location

United States

Company Website

arcinstitute.org/tools/evo/evo-designer

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