Invented by Mark Yandell, Martin Reese, Chad Huff, Hao Hu, Marvin Moore, Fabric Genomics Inc, University of Utah Research Foundation UURF

The market for variant annotation, analysis, and selection tools has witnessed significant growth in recent years, driven by advancements in genomic research and personalized medicine. These tools play a crucial role in identifying and interpreting genetic variations, enabling researchers and clinicians to make informed decisions regarding disease diagnosis, treatment, and prevention. Variant annotation tools are designed to annotate genetic variants, providing information about their functional impact, population frequency, and clinical significance. These tools integrate vast databases of genomic information, such as the Genome Aggregation Database (gnomAD) and the 1000 Genomes Project, to compare and classify variants based on various criteria. They help researchers and clinicians understand the potential implications of genetic variations on an individual’s health, guiding the development of personalized treatment plans. Analysis tools are essential for interpreting the vast amount of genomic data generated through next-generation sequencing technologies. These tools use sophisticated algorithms and statistical models to identify and prioritize potentially pathogenic variants. They consider various factors, including variant type, location, and predicted functional impact, to distinguish between benign and disease-causing variants. By filtering and prioritizing variants, these tools save time and resources, enabling researchers to focus on the most relevant genomic variations. Selection tools aid in the selection of variants for downstream functional studies or clinical applications. They assist in filtering out common variants that are unlikely to have a significant impact on disease risk or treatment response. These tools consider factors such as allele frequency, conservation across species, and predicted functional consequences to prioritize variants with the highest potential for clinical relevance. By narrowing down the list of variants, selection tools facilitate the identification of key genetic variations that can be further investigated or targeted for therapeutic interventions. The market for variant annotation, analysis, and selection tools is driven by the increasing demand for personalized medicine and precision oncology. As genomic sequencing becomes more affordable and accessible, there is a growing need for robust and user-friendly tools that can handle the massive amount of genomic data generated. These tools enable researchers and clinicians to uncover the underlying genetic causes of diseases, identify potential therapeutic targets, and predict treatment response, ultimately leading to improved patient outcomes. Several companies and academic institutions are actively developing and commercializing variant annotation, analysis, and selection tools. Some of the prominent players in this market include Illumina, Qiagen, Golden Helix, and Genomatix. These companies offer a wide range of software solutions that cater to different needs, from basic variant annotation to advanced variant prioritization and interpretation. In conclusion, the market for variant annotation, analysis, and selection tools is experiencing rapid growth due to the increasing demand for personalized medicine and precision oncology. These tools are essential for interpreting and prioritizing genetic variants, enabling researchers and clinicians to make informed decisions regarding disease diagnosis, treatment, and prevention. As genomic research continues to advance, the market for these tools is expected to expand further, driving innovation and improving patient care.

The Fabric Genomics Inc, University of Utah Research Foundation UURF invention works as follows

Disclosed is a method for detecting phenotype-causing genetic variants, and software tools that are related. The methods combine genomic feature-based analysis with sequence characteristics, such as amino acid substation. The methods are applicable to any genomics study, including rare and common disease gene detection, tumor growth mutations detection, personalized medicine and centennial analyses.

Background for Variant annotation, analysis and selection tools

INCORPORATION BY RESEARCH

EXAMPLES

Example 1: Methods

Example 2

VAAST Scores

Example 3

Comparison of AAS approaches

Example 4

Population Stratification.

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Platform Errors

Example 6

Variant Masking

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Identification and variation of genes that cause rare diseases

Example 8

Benchmarking 100 different known disease genes

Example 9

Identification and Variation of Genes Causing Common Multigenic Diseases”.

Example 10

Discussion

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