Identifying Co-associating Bioattributes

• US 20080228677A1
• Filed: 01/03/2008
• Published: 09/18/2008
• Est. Priority Date: 03/16/2007
• Status: Abandoned Application

• Current Assignee: 23andme Incorporated (23andMe Holding Co.)
• Original Assignee: Expanse Networks, Inc.
• Inventors: Eldering, Charles Anthony, Kenedy, Andrew Alexander
• Application Number:
  US11/968,990
• Publication Number:
  US 20080228677A1
• Time in Patent Office: Days
• US Class Current: 706/13
• CPC Class Codes: G06F 16/00 Information retrieval; Database structures therefor; File system structures therefor
• CPC Class Codes: G06F 16/2282 Tablespace storage structures; Management thereof
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9538 Presentation of query results
• CPC Class Codes: G06F 16/955 using information identifiers, e.g. uniform resource locators [URL]
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G09B 19/00 Teaching not covered by other main groups of this subclass teaching or practice apparatus for gun-aiming or gun-laying F41G3/26
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 20/20 Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• CPC Class Codes: G16B 20/40 Population genetics; Linkage disequilibrium
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/70 : for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16H 70/20 : relating to practices or guidelines
• CPC Class Codes: H04L 67/306 : User profiles

Abstract

A bioinformatics method, software, database and system are presented in which combinations of bioattributes comprising pangenetic and non-pangenetic attributes that co-associate with a query attribute (i.e., an attribute of interest) are identified from a database containing attribute combinations and corresponding frequencies of occurrence of each of the attribute combinations for a group of query-attribute-positive individuals and for a group of query-attribute-negative individuals.

Claims

1. A bioinformatics method for identifying combinations of pangenetic and non-pangenetic attributes that co-associate with a query attribute, comprising:

a) receiving a query attribute;

b) accessing a set containing attribute combinations and frequencies of occurrence of the attribute combinations for a set of attribute profiles associated with a group of query-attribute-positive individuals and for a set of attribute profiles associated with a group of query-attribute-negative individuals, wherein each of the attribute combinations contains at least one pangenetic attribute and at least one non-pangenetic attribute;

c) identifying, based on the frequencies of occurrence, attribute combinations that co-associate with the query attribute; and

d) transmitting at least one of the identified attribute combinations as output to indicate combinations of pangenetic and non-pangenetic attributes that co-associate with the query attribute.

2. The bioinformatics method of claim 1, wherein the output is transmitted to at least one destination selected from the group consisting of a user, a database, a dataset, a computer readable memory, a computer readable medium, a computer processor, a computer network, a printout device, a visual display, and a wireless receiver.

3. The bioinformatics method of claim 1, wherein identifying attribute combinations that co-associate with the query attribute in step (c) further comprises identifying each of the attribute combinations having a higher frequency of occurrence for the set of attribute profiles associated with the group of query-attribute-positive individuals than for the set of attribute profiles associated with the group of query-attribute-negative individuals.

4. The bioinformatics method of claim 1, wherein the identified attribute combinations transmitted as output lack one or more user specified attributes.

5. The bioinformatics method of claim 1, wherein the query attribute is a combination of two or more attributes.

6. The bioinformatics method of claim 1, wherein identifying attribute combinations that co-associate with the query attribute in step (c) further comprises i) computing, based on the frequencies of occurrence, corresponding statistical results for the attribute combinations to indicate the strength of association of each of the attribute combinations with the query attribute, and ii) identifying attribute combinations having corresponding statistical results that meet at least one predetermined statistical threshold as attribute combinations that co-associate with the query attribute.

7. The bioinformatics method of claim 6, wherein transmitting at least one of the identified attribute combinations as output in step (d) further comprises transmitting a tabulation of the identified attribute combinations and the corresponding statistical results to indicate the identified attribute combinations that are most likely to co-associate with the query attribute.

8. The bioinformatics method of claim 6, wherein transmitting at least one of the identified attribute combinations as output in step (d) further comprises transmitting a rank-ordered tabulation of one or more of the identified attribute combinations to indicate the identified attribute combinations that are most likely to co-associate with the query attribute, wherein the rank of each of the identified attribute combinations in the tabulation is based on the attribute content of each of the identified attribute combinations and the strength of association of each of the identified attribute combinations with the query attribute.

9. The bioinformatics method of claim 8, wherein the identified attribute combinations transmitted as output are selected for transmission as output based on a predetermined threshold applied to rank.

10. The bioinformatics method of claim 1, further comprising:

e) associating the output with an individual and storing the association.

11. The bioinformatics method of claim 1, wherein each of the attribute combinations contains at least one pangenetic attribute, at least one physical attribute, at least one behavioral attribute, and at least one situational attribute.

12. A program storage device readable by a machine and containing a set of instructions which, when read by the machine, causes execution of a bioinformatics method for identifying combinations of pangenetic and non-pangenetic attributes that co-associate with a query attribute, comprising:

a) receiving a query attribute;

b) accessing a set containing attribute combinations and frequencies of occurrence of the attribute combinations for a set of attribute profiles associated with a group of query-attribute-positive individuals and for a set of attribute profiles associated with a group of query-attribute-negative individuals, wherein each of the attribute combinations contains at least one pangenetic attribute and at least one non-pangenetic attribute;

c) identifying, based on the frequencies of occurrence, attribute combinations that co-associate with the query attribute; and

d) transmitting at least one of the identified attribute combinations as output to indicate combinations of pangenetic and non-pangenetic attributes that co-associate with the query attribute.

13. The program storage device of claim 12, wherein identifying attribute combinations that co-associate with the query attribute in step (c) further comprises identifying each of the attribute combinations having a higher frequency of occurrence for the set of attribute profiles associated with the group of query-attribute-positive individuals than for the set of attribute profiles associated with the group of query-attribute-negative individuals.

14. The program storage device of claim 12, wherein identifying attribute combinations that co-associate with the query attribute in step (c) further comprises i) computing, based on the frequencies of occurrence, corresponding statistical results for the attribute combinations to indicate the strength of association of each of the attribute combinations with the query attribute, and ii) identifying attribute combinations having corresponding statistical results that meet at least one predetermined statistical threshold as attribute combinations that co-associate with the query attribute.

15. A bioinformatics database system for identifying combinations of pangenetic and non-pangenetic attributes that co-associate with a query attribute, comprising:

a) a memory containing;

i) a first data structure containing attribute combinations and frequencies of occurrence of the attribute combinations for a set of attribute profiles associated with a group of query-attribute-positive individuals and for a set of attribute profiles associated with a group of query-attribute-negative individuals, wherein each of the attribute combinations contains at least one pangenetic attribute and at least one non-pangenetic attribute;

b) a processor for;

i) receiving the query attribute;

ii) accessing the first data structure;

iii) identifying, based on the frequencies of occurrence, attribute combinations contained in the first data structure that co-associate with the query attribute; and

iv) transmitting at least one of the identified attribute combinations as output to indicate combinations of pangenetic and non-pangenetic attributes that co-associate with the query attribute.

16. The bioinformatics database system of claim 15, wherein identifying attribute combinations contained in the first data structure that co-associate with the query attribute further comprises identifying each of the attribute combinations having a higher frequency of occurrence for the set of attribute profiles associated with the group of query-attribute-positive individuals than for the set of attribute profiles associated with the group of query-attribute-negative individuals.

17. The bioinformatics database system of claim 15, wherein identifying attribute combinations that co-associate with the query attribute further comprises computing, based on the frequencies of occurrence, corresponding statistical results for the attribute combinations to indicate the strength of association of each of the attribute combinations with the query attribute, and identifying attribute combinations having corresponding statistical results that meet at least one predetermined statistical threshold as attribute combinations that co-associate with the query attribute.

18. A bioinformatics computer-based system for identifying combinations of pangenetic and non-pangenetic attributes that co-associate with a query attribute, comprising:

a) a first data communications subsystem for receiving a query attribute;

b) a data accessing subsystem for accessing a set containing attribute combinations and frequencies of occurrence of the attribute combinations for a set of attribute profiles associated with a group of query-attribute-positive individuals and for a set of attribute profiles associated with a group of query-attribute-negative individuals, wherein each of the attribute combinations contains at least one pangenetic attribute and at least one non-pangenetic attribute;

c) a data processing subsystem for identifying, based on the frequencies of occurrence, attribute combinations that co-associate with the query attribute; and

d) a second data communications subsystem for transmitting at least one of the identified attribute combinations as output to indicate combinations of pangenetic and non-pangenetic attributes that co-associate with the query attribute.

19. The bioinformatics computer-based system of claim 18, wherein identifying attribute combinations that co-associate with the query attribute further comprises identifying each of the attribute combinations having a higher frequency of occurrence for the set of attribute profiles associated with the group of query-attribute-positive individuals than for the set of attribute profiles associated with the group of query-attribute-negative individuals.

20. The bioinformatics computer-based system of claim 18, wherein identifying attribute combinations that co-associate with the query attribute further comprises i) computing, based on the frequencies of occurrence, corresponding statistical results for the attribute combinations to indicate the strength of association of each of the attribute combinations with the query attribute, and ii) identifying attribute combinations having corresponding statistical results that meet at least one predetermined statistical threshold as attribute combinations that co-associate with the query attribute.