John J Macpherson

US Patent:

8510057, Aug 13, 2013

Filed:

May 8, 2008

Appl. No.:

12/151977

Inventors:

Linda Avey - Los Gatos CA, US
Andro Rene Hsu - Berkeley CA, US
Oleksiy Khomenko - Stanford CA, US
John Michael Macpherson - Palo Alto CA, US
Joanna Louise Mountain - Menlo Park CA, US
Brian Thomas Naughton - Mountain View CA, US
Serge Saxonov - Seattle WA, US
Anne Wojcicki - Palo Alto CA, US
Alexander Wong - Palo Alto CA, US

Assignee:

23andMe, Inc. - Mountain View CA

International Classification:

G06F 7/00

US Classification:

702 19, 702 20, 703 11, 707700, 436501

Abstract:

Summarizing an aggregate contribution to a characteristic for an individual is disclosed, including determining the characteristic to be evaluated, identifying one or more markers associated with the characteristic, retrieving the measurement of the individual for each of the one or more markers from a database of individuals' markers, retrieving a statistical factor that measures the association between the marker associated with the characteristic and the characteristic for each of the one or more markers from the marker database, and determining the aggregate contribution based at least in part on the retrieved statistical factors.

US Patent:

20210375392, Dec 2, 2021

Filed:

May 27, 2021

Appl. No.:

17/303398

Inventors:

- Sunnyvale CA, US
Jianan Zhan - Santa Clara CA, US
Manoj Ganesan - Sunnyvale CA, US
Austin William Marshall - Los Gatos CA, US
James Rowan Ashenhurst - San Francisco CA, US
Derrick Poo-Ray Kondo - Belmont CA, US
Shiva Amiri - Sunnyvale CA, US
Subarnarekha Sinha - Los Altos CA, US
Sanjeev Suresh - Saratoga CA, US
John Michael Macpherson - Santa Ana CA, US
Bertram Lorenz Koelsch - Salt Lake City UT, US
Cordell T. Blakkan - San Francisco CA, US
Shannon M. Hamilton - San Mateo CA, US

International Classification:

G16B 20/20
G16H 50/30
G16B 5/00

Abstract:

The disclosed embodiments concern methods, apparatus, systems, and computer program products for developing polygenic risk score (PRS) models. In some implementations, a fully automated process is provided that allows for a PRS model to be defined by an initial set of parameters. In some implementations the PRS models are trained to provide a PRS for particular populations.

US Patent:

20190384777, Dec 19, 2019

Filed:

Aug 28, 2019

Appl. No.:

16/554212

Inventors:

- Mountain View CA, US
Chuong Do - Mountain View CA, US
John Michael Macpherson - Santa Ana CA, US

International Classification:

G06F 16/28
G16B 50/00

Abstract:

Databases and data processing systems for use with a network-based personal genetics services platform may include member information pertaining to a plurality of members of the network-based personal genetics services platform. The member information may include genetic information, family history information, environmental information, and phenotype information of the plurality of members. A data processing system may determine, based at least in part on the member information, a model for predicting a phenotype from genetic information, family history information, and environmental information, wherein determining the model includes training the model using the member information pertaining to a set of the plurality of members. The data processing system may also receive a request from a questing member to predict a phenotype of interest, and apply an individual's genetic information, family history information, and environmental information to the model to obtain a prediction associated with the phenotype of interest for the requesting member.

US Patent:

20190114219, Apr 18, 2019

Filed:

Apr 10, 2018

Appl. No.:

15/950023

Inventors:

- Mountain View CA, US
Eric Durand - Sceaux, FR
John Michael Macpherson - Mountain View CA, US

International Classification:

G06F 11/07
G06N 7/00

Abstract:

Error correction in ancestry classification includes obtaining, from a classifier, initial ancestry classifications associated with portions of two phased haplotypes of a chromosome pair of an individual; performing error correction on an initial ancestry classification, including detecting a phasing error in the initial ancestry classifications; and outputting a corrected ancestry classification in which the phasing error is corrected.

US Patent:

20180307778, Oct 25, 2018

Filed:

Jun 27, 2018

Appl. No.:

16/020864

Inventors:

- Mountain View CA, US
John Michael Macpherson - Mountain View CA, US

International Classification:

G06F 17/30
G06F 19/00
G16H 10/60
G06F 19/10

Abstract:

Determining relative connections between individuals includes: obtaining identification information of a first individual and identification information of a second individual; determining, based at least in part on a relative connections graph, a relative connections path connecting the first individual, the second individual, and at least one additional individual; and outputting information pertaining to the relative connections path.

US Patent:

20170329866, Nov 16, 2017

Filed:

Jun 5, 2013

Appl. No.:

13/910890

Inventors:

- Mountain View CA, US
John Michael Macpherson - Mountain View CA, US

International Classification:

G06F 17/30

Abstract:

Determining relative connections between individuals includes: obtaining identification information of a first individual and identification information of a second individual; determining, based at least in part on a relative connections graph, a relative connections path connecting the first individual, the second individual, and at least one additional individual; and outputting information pertaining to the relative connections path.

US Patent:

20170329904, Nov 16, 2017

Filed:

May 10, 2016

Appl. No.:

15/151404

Inventors:

- Mountain View CA, US
Chuong Do - Mountain View CA, US
John Michael Macpherson - Santa Ana CA, US

International Classification:

G06F 19/00
G06F 17/30
G06F 19/28
G06F 19/00

Abstract:

Databases and data processing systems for use with a network-based personal genetics services platform may include member information pertaining to a plurality of members of the network-based personal genetics services platform. The member information may include genetic information, family history information, environmental information, and phenotype information of the plurality of members. A data processing system may determine, based at least in part on the member information, a model for predicting a phenotype from genetic information, family history information, and environmental information, wherein determining the model includes training the model using the member information pertaining to a set of the plurality of members. The data processing system may also receive a request from a questing member to predict a phenotype of interest, and apply an individual's genetic information, family history information, and environmental information to the model to obtain a prediction associated with the phenotype of interest for the requesting member.

US Patent:

20170277828, Sep 28, 2017

Filed:

Jun 13, 2017

Appl. No.:

15/621985

Inventors:

- Mountain View CA, US
Andro Rene Hsu - Mountain View CA, US
Oleksiy Khomenko - Mountain View CA, US
John Michael Macpherson - Mountain View CA, US
Joanna Louise Mountain - Mountain View CA, US
Brian Thomas Naughton - Mountain View CA, US
Serge Saxonov - Oakland CA, US
Anne Wojcicki - Mountain View CA, US
Alexander Wong - Mountain View CA, US

International Classification:

G06F 19/24
G06F 19/18

Abstract:

Summarizing an aggregate contribution to a phenotypic characteristic for an individual includes: receiving information pertaining to the phenotypic characteristic of an individual; identifying, using one or more computer processors, a set of one or more markers associated with the phenotypic characteristic; obtaining a set of one or more marker measurements of the individual that corresponds to the set of one or more markers; obtaining a set of one or more statistical factors that measure associations between the set of one or more markers and the phenotypic characteristic; determining an aggregate contribution to the phenotypic characteristic of the individual based at least in part on the retrieved set of one or more statistical factors; and outputting a display characteristic to be displayed that is associated with the aggregate contribution to the phenotypic characteristic for the individual.