# US 2021/0174232 A1 · System, method, and computer software product for genotype determination using probe array data

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- Number: US 2021/0174232 A1
- Document ID: US20210174232A1
- Status: Published application
- Kind: A1
- Application number: 17/093,571
- Filed: 2020-11-09
- Published: 2021-06-10
- Earliest claimed: 2007-05-18
- Assignees: Affymetrix, Inc.
- Applicants: Affymetrix, Inc.
- Inventors: Earl A. Hubbell; Simon Cawley
- Web page: https://patentgrep.com/patent/US20210174232A1

## CPC

- G16B 20/20: Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
- G06F 30/327: Logic synthesis; Behaviour synthesis, e.g. mapping logic, HDL to netlist, high-level language to RTL or netlist
- G06N 20/00: Machine learning
- G16B 20/00: ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
- G16B 40/30: Unsupervised data analysis
- G16B 20/10: Ploidy or copy number detection
- G16B 20/40: Population genetics; Linkage disequilibrium
- G16B 25/00: ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
- G16B 40/00: ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
- G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS

## Abstract

An embodiment of a method of analyzing data from processed images of biological probe arrays is described that comprises receiving a plurality of files comprising a plurality of intensity values associated with a probe on a biological probe array; normalizing the intensity values in each of the data files; determining an initial assignment for a plurality of genotypes using one or more of the intensity values from each file for each assignment; estimating a distribution of cluster centers using the plurality of initial assignments; combining the normalized intensity values with the cluster centers to determine a posterior estimate for each cluster center; and assigning a plurality of genotype calls using a distance of the one or more intensity values from the posterior estimate.

## Claims

### Claim 1

A method for calling genotypes from a probe array experiment, comprising:
contacting a genotyping probe array with a DNA sample to obtain a hybridized sample;
obtaining hybridization intensity information from the hybridized sample;
normalizing probe intensity data;
transforming the data by clustering the data for each genetic loci of interest to obtain transformed data;
dividing the transformed data into trial genotypes by generating genotyping calls;
calculating the highest log-likelihood of data; and
assigning a genotype to the data.

### Claim 2 (depends on 1)

The method of claim 1 wherein the array comprises more than 1 million different sequence probes and wherein each probe is perfectly complementary to an allele of a SNP that has a minor allele frequency of at least 2% in a population.

### Claim 3

A method for determining the genotype of a nucleic acid sample at a plurality of SNPs, comprising: (a) hybridizing said nucleic acid sample to an array of allele specific probes to obtain raw probe intensity measurements; (b) normalizing said raw probe intensity measurements to obtain normalized probe intensities; performing an allele summarization to obtain allele signal estimates; (c) transforming said allele signal estimates in clustering space to obtain transformed allele signal estimates; (d) generating seed genotypes from said raw probe intensity measurements to obtain initial genotype estimates; (e) fit prior across multiple SNPs using initial genotype estimates and transformed allele signal estimates to obtain prior for cluster characteristics; and (f) update the cluster characteristics using a Bayesian update to obtain posterior for cluster characteristics; and make genotype calls to obtain the genotype of the nucleic acid sample at a plurality of SNPs.

### Claim 4 (depends on 3)

The method of claim 3 further comprising obtaining confidence values for each of the genotype calls.