# US 8,571,807 B2 · Computer algorithm for automatic allele determination from fluorometer genotyping device

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- Number: US 8,571,807 B2
- Document ID: US8571807B2
- Status: Granted
- Kind: B2
- Application number: 13/308,623
- Filed: 2011-12-01
- Published: 2012-06-07
- Granted: 2013-10-29
- Earliest claimed: 2002-03-01
- Assignees: Applied Biosystems, LLC
- Applicants: Stephen Glanowski; Jeremy Heil; Emily S. Winn-Deen; Ivy A. McMullen
- Inventors: Stephen Glanowski; Jeremy Heil; Emily S. Winn-Deen; Ivy A. McMullen
- Web page: https://patentgrep.com/patent/US8571807B2

## CPC

- G06F 16/285: {Clustering or classification}
- G16B 20/00: ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
- G16B 20/20: Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
- G16B 20/40: Population genetics; Linkage disequilibrium
- G16B 40/10: Signal processing, e.g. from mass spectrometry [MS] or from PCR
- 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
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY

## Abstract

The present invention provides methods and systems for an automated method of identifying allele values from data files derived from processed fluorophore emissions detected during the observation of fluorophore labeled nucleotide probes used in analyzing polymorphic DNA are provided. These methods are used in the rapid and efficient distinguishing of targeted polymorphic DNA sites without control samples.

## Claims

### Claim 1

A method for categorizing a dataset comprising a plurality of datapoints, the method comprising:
receiving the plurality of datapoints from a fluorometric genotyping detection instrument, wherein the plurality of datapoints corresponds to a plurality of amplified samples;
generating a plurality of angular values by calculating an angular value for each datapoint based on numerical values of each data point;
generating a plurality of angular difference values by calculating differences between adjacent angular values;
determining at least one category-dividing value by identifying at least one difference value above a predetermined threshold gap value;
classifying at least one datapoint according to its angular value relative to at least one category-dividing value; and
providing a classification result based at least in part on the at least one category-dividing value.

### Claim 2 (depends on 1)

The method of claim 1 wherein each datapoint comprises two numerical values.

### Claim 3 (depends on 2)

The method of claim 2 wherein the angular value is an arctangent of the two numerical values.

### Claim 4 (depends on 1)

The method of claim 1 wherein the numerical values comprise fluorometric data.

### Claim 5 (depends on 1)

The method of claim 1 wherein the determining identifies two category-dividing values comprising a first and a second category-dividing value.

### Claim 6 (depends on 1)

The method of claim 1 further comprising normalizing the numerical values to a scale.

### Claim 7 (depends on 6)

The method of claim 6 wherein the scale ranges from 0.0 to 1.0.

### Claim 8 (depends on 1)

The method of claim 1, further comprising removing non-amplification datapoints from the dataset, wherein removing the non-amplified datapoints from the data set include:
calculating a Euclidean distance for each datapoint; and
removing at least one datapoint from the dataset, wherein the Euclidean distance of the datapoint falls below a predetermined distance threshold.

### Claim 9 (depends on 5)

The method of claim 5 wherein the instructions for classifying the at least one datapoint further comprises:
classifying at least one datapoint in a first category, wherein all datapoints of the first category have an angular value lower than the first and second category-dividing values;
classifying at least one datapoint in a second category, wherein all datapoints of the second category have an angular value between the first and second category-dividing values; and
classifying at least one datapoint in a third category, wherein all datapoints of the third category have an angular value greater than the first and second category-dividing values.

### Claim 10 (depends on 9)

The method of claim 9 wherein classification in the first category corresponds to homozygosity for a first allele, classification in the third category corresponds to homozygosity for a second allele, and classification in the second category corresponds to heterozygosity for the first and second alleles.

### Claim 11 (depends on 10)

The method of claim 10 further comprising determining the presence of a condition to bring to the attention of a human user, wherein the condition comprises the proportion of datapoints classified as heterozygous exceeding a predetermined threshold.