# US 2014/0207436 A1 · Feature selection for efficient epistasis modeling for phenotype prediction > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2014/0207436 A1 - Document ID: US20140207436A1 - Status: Published application - Kind: A1 - Application number: 14/030,743 - Filed: 2013-09-18 - Published: 2014-07-24 - Earliest claimed: 2013-01-21 - Assignees: International Business Machines Corporation - Applicants: International Business Machines Corporation - Inventors: David HAWS; Dan HE; Laxmi P. PARIDA - Web page: https://patentgrep.com/patent/US20140207436A1 ## CPC - G16B 5/20: Probabilistic models - G16B 5/00: ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks - 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 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 ## Abstract Various embodiments select markers for modeling epistasis effects. In one embodiment, a processor receives a set of genetic markers and a phenotype. A relevance score is determined with respect to the phenotype for each of the set of genetic markers. A threshold is set based on the relevance score of a genetic marker with a highest relevancy score. A relevance score is determined for at least one genetic marker in the set of genetic markers for at least one interaction between the at least one genetic marker and at least one other genetic marker in the set of genetic markers. The at least one interaction is added to a top-k feature set based on the relevance score of the at least one interaction satisfying the threshold. ## Claims ### Claim 1 An information processing system for selecting markers for modeling epistasis effects, the computer implemented method comprising: a memory; a processor communicatively coupled to the memory; and a feature selection module coupled to the memory and the processor, wherein the feature selection module is configured to perform a method comprising: receiving, by a processor, a set of genetic markers and a phenotype; determining, for each of the set of genetic markers, a relevance score with respect to the phenotype; setting a threshold based on the relevance score of a genetic marker in the set of genetic markers with a highest relevancy score; determining, for at least one genetic marker in the set of genetic markers, a relevance score for at least one interaction between the at least one genetic marker and at least one other genetic marker in the set of genetic markers; and adding the at least one interaction to a top-k feature set based on the relevance score of the at least one interaction satisfying the threshold, wherein each feature in the top-k feature set is one of a genetic maker and an interaction each comprising a top-k relevance score. ### Claim 2 (depends on 1) The information processing system of claim 1, wherein the method further comprises: randomly sampling a subset of genetic markers from the set of genetic markers; and selecting the at least one additional genetic marker from the subset of genetic markers. ### Claim 3 (depends on 2) The information processing system of claim 2, wherein determining the relevance score of the at least one interaction comprises: determining a first set of relevance scores comprising a relevance score with respect to the phenotype for each of a first plurality of interactions between the at least one genetic marker and each of the subset of genetic markers; determining, based on a normal distribution associated with the first set of relevance scores, a probability of the at least one genetic marker being associated with an interaction comprising a relevance score greater than the threshold; comparing the probability to a probability threshold; and determining, based on the probability satisfying the probability threshold, a second set of relevance scores comprising a relevance score for each of a second plurality of interactions between the at least one genetic marker and a remaining set of genetic markers in the set of genetic markers, wherein the second plurality of interactions comprises the at least one interaction, and wherein the remaining set of genetic markers comprises the at least one additional genetic marker. ### Claim 4 (depends on 1) The information processing system of claim 1, wherein the method further comprises: generating, based on adding the at least one interaction to the top-k feature set, an updated top-k feature set by removing one of a genetic marker and an interaction associated with a lowest relevance score from the top-k feature set. ### Claim 5 (depends on 1) The information processing system of claim 1, wherein the method further comprises: updating the threshold according to a highest relevance score associated with one of a genetic marker and an interaction within the updated top-k feature; determining a relevance score for at least one additional interaction between the at least one genetic marker and at least one other genetic marker in the set of genetic markers; comparing the relevance score of at least one additional interaction to the threshold that has been updated; and adding the at least one additional interaction to the top-k feature set based on the relevance score of the at least one additional interaction satisfying the threshold that has been updated. ### Claim 6 A non-transitory computer program product for selecting markers for modeling epistasis effects, the computer program product comprising: a storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: receiving, by a processor, a set of genetic markers and a phenotype; determining, for each of the set of genetic markers, a relevance score with respect to the phenotype; setting a threshold based on the relevance score of a genetic marker in the set of genetic markers with a highest relevancy score; determining, for at least one genetic marker in the set of genetic markers, a relevance score for at least one interaction between the at least one genetic marker and at least one other genetic marker in the set of genetic markers; and adding the at least one interaction to a top-k feature set based on the relevance score of the at least one interaction satisfying the threshold, wherein each feature in the top-k feature set is one of a genetic maker and an interaction each comprising a top-k relevance score. ### Claim 7 (depends on 6) The non-transitory computer program product of claim 6, wherein the method further comprises: randomly sampling a subset of genetic markers from the set of genetic markers; and selecting the at least one additional genetic marker from the subset of genetic markers. ### Claim 8 (depends on 7) The non-transitory computer program product of claim 7, wherein determining the relevance score of the at least one interaction comprises: determining a first set of relevance scores comprising a relevance score with respect to the phenotype for each of a first plurality of interactions between the at least one genetic marker and each of the subset of genetic markers; determining, based on a normal distribution associated with the first set of relevance scores, a probability of the at least one genetic marker being associated with an interaction comprising a relevance score greater than the threshold; comparing the probability to a probability threshold; and determining, based on the probability satisfying the probability threshold, a second set of relevance scores comprising a relevance score for each of a second plurality of interactions between the at least one genetic marker and a remaining set of genetic markers in the set of genetic markers, wherein the second plurality of interactions comprises the at least one interaction, and wherein the remaining set of genetic markers comprises the at least one additional genetic marker. ### Claim 9 (depends on 6) The non-transitory computer program product of claim 6, wherein the method further comprises: generating, based on adding the at least one interaction to the top-k feature set, an updated top-k feature set by removing one of a genetic marker and an interaction associated with a lowest relevance score from the top-k feature set. ### Claim 10 (depends on 6) The non-transitory computer program product of claim 6, wherein the method further comprises: updating the threshold according to a highest relevance score associated with one of a genetic marker and an interaction within the updated top-k feature. ### Claim 11 (depends on 10) The non-transitory computer program product of claim 10, wherein the method further comprises: determining a relevance score for at least one additional interaction between the at least one genetic marker and at least one other genetic marker in the set of genetic markers; comparing the relevance score of at least one additional interaction to the threshold that has been updated; and adding the at least one additional interaction to the top-k feature set based on the relevance score of the at least one additional interaction satisfying the threshold that has been updated.