METHOD FOR ANALYZING AND DISPLAYING GENETIC INFORMATION BETWEEN FAMILY MEMBERS
A technique of using collaborative family medical history (CFMH) to estimate disease risk includes establishing CFMH information of a user and a plurality of relatives of the user, the CFMH information including genetic information of at least some of the family members, genetic information of the user, or both. It further includes analyzing the CFMH information, including the genetic information. It further includes determining a potential risk condition of the user and a potential risk condition of at least a family member based on the CFMH information. It also includes outputting the potential risk condition of the user and the potential risk condition of the at least one family member.
1 . A computer-implemented method comprising:
displaying, a user interface associated with a family tree, wherein each individual within a family history is arranged as a node within the family tree;
receiving, by the user interface, genetic information related to one or more of the individuals within the family tree;
in response to a selection of the node corresponding to one individual within the family tree, determining a phenotype model based on the received genetic information, a family history based on the family tree, and environmental information associated with one or more of the individuals within the family tree, wherein the determining includes:
performing a logistic regression such that the received genetic information and environmental information is encoded as a multidimensional vector;
wherein the encoding identifies one or more features including representations of alleles as part of the multidimensional vector;
identifying a likelihood of a phenotype associated with the selected node, wherein the identified likelihood of the phenotype is based on the alleles and the one or more features of the multidimensional vector; and
generating, within the user interface, a graphical indication of the identified phenotype, wherein the graphical indication includes at least one node within the family tree.
2 . The computer-implemented method of claim 1 , wherein identifying the likelihood of the phenotype includes identifying at least one of: the likelihood of a disease occurring over an individual's lifetime, a likelihood of the disease occurring within a specific time frame, or a likelihood that the individual currently has the disease.
3 . The computer-implemented method of claim 1 , wherein the identified phenotype is a non-disease related trait.
4 . The computer-implemented method of claim 1 , wherein the logistic regression is based on a set of data comprising, for each individual of a plurality of individuals, one or more of: genetic information, family history information, and environmental information.
5 . The computer-implemented method of claim 1 , wherein the logistic regression accounts for genetic information shared by the user and the one or more relatives.
6 . The computer-implemented method of claim 1 , wherein the generated graphical indication reflects two or more of the individuals within the family tree.
7 . The computer-implemented method of claim 1 , wherein the received genetic information includes a disease condition of the one or more relatives.
8 . The computer-implemented method of claim 1 , wherein the received genetic information includes genetic information of the one or more relatives.
9 . The computer-implemented method of claim 1 , wherein the received genetic information includes information associated with drug side-effects.
10 . The computer-implemented method of claim 1 , wherein the genetic information includes genotype information.
11 . The computer-implemented method of claim 1 , wherein generating the graphical indication displaying on the user interface an editable field, a dropdown menu, or a search box for querying a database.
12 . The computer-implemented method of claim 1 further comprising communicating a notification of the graphical indication to one or more of the individuals within the family tree.
13 . The computer-implemented method of claim 1 , wherein the graphical indication includes a reason for the likelihood of the phenotype.
14 . The computer-implemented method of claim 1 , wherein the one or more of the individuals within the family tree share at least one common ancestor with the user.
15 . A non-transitory computer readable medium having stored therein instructions executable by one or more processors, including instructions executable to:
display, a user interface associated with a family tree, wherein each individual within a family history is arranged as a node within the family tree;
receive, by the user interface, genetic information related to one or more of the individuals within the family tree;
in response to a selection of the node corresponding to one individual within the family tree, determine a phenotype model based on the received genetic information, a family history based on the family tree, and environmental information associated with one or more of the individuals within the family tree, wherein the determination includes instructions executable to:
perform a logistic regression such that the received genetic information and environmental information is encoded as a multidimensional vector;
wherein the encoding identifies one or more features including representations of alleles as part of the multidimensional vector;
identify a likelihood of a phenotype associated with the selected node, wherein the identified likelihood of the phenotype is based on the alleles and the one or more features of the multidimensional vector; and
generate, within the user interface, a graphical indication of the identified phenotype, wherein the graphical indication includes at least one node within the family tree.
16 . The non-transitory computer readable medium of claim 15 , wherein identifying the likelihood of the phenotype includes identifying at least one of: the likelihood of a disease occurring over an individual's lifetime, a likelihood of the disease occurring within a specific time frame, or a likelihood that the individual currently has the disease.
17 . The non-transitory computer readable medium of claim 15 , wherein the identified phenotype is a non-disease related trait.
18 . The non-transitory computer readable medium of claim 15 , wherein the logistic regression is based on a set of data comprising, for each individual of a plurality of individuals, one or more of: genetic information, family history information, and environmental information.
19 . The non-transitory computer readable medium of claim 15 , wherein the logistic regression accounts for genetic information shared by the user and the one or more relatives.
20 . The non-transitory computer readable medium of claim 15 , wherein the generated graphical indication reflects two or more of the individuals within the family tree.