US 11,309,062 B2 · Hierarchical optimized detection of relatives

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.

Claims18

Dependent claims

A method of determining whether a sample of DNA contains related contributors, comprising the steps of:

receiving peak detection signals for a predetermined number of loci in a DNA sample;
establishing from the peak detection signals a first set of peak detection data to be transformed and a second set of peak detection data to remain untransformed;
transforming the first set of peak detection data using at least one of a plurality of transformation approaches;
inputting the transformed first set of peak detection data and untransformed second set of peak detection data into a trained machine learning algorithm to produce a probability for each locus in the DNA sample that there were multiple, genetically related contributors.

1 more element

Dependencies are inferred from the claim text.

Hierarchical optimized detection of relatives

Life of this patent

Hierarchical optimized detection of relatives

Life of this patent

Abstract

Claims18