Invention Grant
- Patent Title: Hierarchical optimized detection of relatives
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Application No.: US16148341Application Date: 2018-10-01
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Publication No.: US11309062B2Publication Date: 2022-04-19
- Inventor: Michael Marciano , Jonathan D. Adelman
- Applicant: Michael Marciano , Jonathan D. Adelman
- Applicant Address: US NY Manlius; US NY Mexico
- Assignee: Michael Marciano,Jonathan D. Adelman
- Current Assignee: Michael Marciano,Jonathan D. Adelman
- Current Assignee Address: US NY Manlius; US NY Mexico
- Agency: Bond Schoeneck and King PLLC
- Agent David Nocilly
- Main IPC: G16B40/00
- IPC: G16B40/00 ; G16B30/00 ; G16B20/20 ; G16H10/20 ; C12Q1/68

Abstract:
A system for evaluating a DNA sample and determining whether the sample contains related individuals and/or unrelated individuals with high levels of alleles sharing. Trained and pre-validated machine learning algorithms are to rapidly and probabilistically assess the presence of relatives in a DNA mixture. To make a probabilistic determination, the system evaluates aspect of the sample that have not be considered before, such as peak heights, peak height ratios, maximum peak heights, minimum peak heights, ratios of allele heights to one another, number of contributors using maximum allele count method, and quantitative measures of the amount of DNA contributed by the male and female organisms. The system identifies whether a DNA sample has contributors that are not readily identifiable based on the data and can thus improve downstream analysis.
Public/Granted literature
- US20190102517A1 HIERARCHICAL OPTIMIZED DETECTION OF RELATIVES Public/Granted day:2019-04-04
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