Myriad Genetics. has filed a patent for a method and system to analyze sex-chromosome aneuploidies in individuals. The method involves training a neural network model and using a machine learning algorithm to determine the sex-chromosome status based on normalized read depth for a gene in the individual’s genome. GlobalData’s report on Myriad Genetics gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Myriad Genetics, Personalized medicine biomarkers was a key innovation area identified from patents. Myriad Genetics's grant share as of January 2024 was 28%. Grant share is based on the ratio of number of grants to total number of patents.
Method for analyzing sex-chromosome aneuploidies using neural network
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A patent application (Publication Number: US20240038339A1) describes a method and system for analyzing sex-chromosome aneuploidies in individuals using a neural network model and machine learning algorithms. The method involves training the neural network model based on predetermined information related to sex chromosomes and determining the sex-chromosome status based on normalized read depth for a gene in the individual's genome. The system includes a neural network model that can provide a twin sex call and determine complex sex phenotypes like vanishing twins and mosaic monosomy. Additionally, the method and system can provide a negative result when the sex-chromosome status is anomalous and determine the status via Bayesian statistics, graphing, or visualization of read depth and allosome data.
The system further includes features such as determining a probability of sex-chromosome status for multiple samples, heuristic data analysis, and expert human review as a truth set. The neural network model can be optimized through automated retraining protocols to synchronize training over time, reduce drift, and validate performance. Confidence levels for the respective sex-chromosome status can also be determined. Overall, the method and system offer a comprehensive approach to analyzing sex-chromosome aneuploidies in individuals, incorporating advanced technologies like neural networks and machine learning algorithms to provide accurate and detailed results for various sex-chromosome statuses and phenotypes.
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