System and method for identification of synergistic interactions from continuous data

Abstract

Systems and methods for selecting factors from a continuous data set of measurements are provided. The measurements include values of factors and/or outcomes. Two or more factors that are jointly associated with one or more outcomes from the data set are identified. Each of the two or more factors are analyzed to determine at least one cooperative interaction among the factors with respect to an outcome. The two or more factors can be a module of factors serving as a single factor participating in a cooperative interaction with another factor or module of factors.

1 . A method for selecting factors from a data set of continuous measurements, the continuous measurements including values of the factors and outcomes, comprising:
 identifying two or more factors that are jointly associated with one or more outcomes from the data set; and   analyzing each of the two or more factors to determine at least one cooperative interaction among the factors with respect to an outcome.   
     
     
         2 . The method of  claim 1 , wherein the two or more factors comprise a module of factors. 
     
     
         3 . The method of  claim 1 , wherein the two or more factors comprise a sub-module of factors. 
     
     
         4 . The method of  claim 1 , wherein the at least one interaction comprises a structure of interactions. 
     
     
         5 . The method of  claim 1 , wherein the two or more factors comprise two or more genes, the data includes continuous gene expression data comprising expression levels for each of the two or more genes, and the one or more outcomes include presence or absence of a disease. 
     
     
         6 . The method of  claim 5 , wherein the two or more genes comprise a module of genes. 
     
     
         7 . The method of  claim 6 , wherein the module of genes comprise a smallest cooperative module of genes with joint expression levels that can be used for a prediction of the presence of a disease. 
     
     
         8 - 16 . (canceled) 
     
     
         17 . A system for selecting factors from a data set of continuous measurements, each measurement comprising values of the factors and outcomes, comprising:
 at least one processor, and   a computer readable medium coupled to the at least one processor, having stored thereon instructions which when executed cause the at least one processor to:
 identify two or more factors that are jointly associated with one or more outcomes or factors from the data; and 
 determine at least one cooperative interaction among the two or more factors with respect to the outcome or the factor. 
   
     
     
         18 . The system of  claim 17 , wherein the two or more factors comprise a module of factors, treated as a single factor. 
     
     
         19 . The system of  claim 18 , wherein the two or more factors comprise a module of factors with two or more genes, the data comprises continuous gene expression data comprising expression levels for each of the two or more genes, and the one or more outcomes comprise the presence or absence of a disease or trait. 
     
     
         20 . The system of  claim 19 , wherein the two or more genes comprise a module of genes. 
     
     
         21 . The system of  claim 20 , wherein the module of genes comprises at least one sub-module of genes to be treated as one factor. 
     
     
         22 . The system of  claim 20 , wherein the module of genes comprises a smallest module of genes that can be used for a prediction of the presence of disease with high accuracy.