# LGRF tests for multiple regions/genes using SSD format files Test the association between an outcome variable and multiple regions/genes using SSD format files. ```r LGRF.SSD.All(SSD.INFO, result.null, Gsub.id=NULL, interGXT=FALSE, similarity='GR', impute.method='fixed', MinP.compare=FALSE, ...) ``` ## Arguments - `SSD.INFO`: SSD format information file, output of function ``Open_SSD". The sets are defined by this file. - `result.null`: Output of function ``null.LGRF". - `Gsub.id`: The subject id corresponding to the genotype matrix, an m dimensional vector. This is in order to match the phenotype and genotype matrix. The default is NULL, where the order is assumed to be matched with Y, X and time. - `interGXT`: Whether to incorperate the gene-time interaction effect. Incorperating this effect can improve power if there is any gene-time interaction, but has slight power loss otherwise. The default is FALSE. *Please note that the second column of time should be included as a covairate when interGXT is TRUE. - `similarity`: Choose the similarity measurement for the genetic variants. Can be either "GR" for genetic relationship or "IBS" for identity by state. The default is "GR" for better computational efficiency. - `impute.method`: Choose the imputation method when there is missing genotype. Can be "random", "fixed" or "bestguess". Given the estimated allele frequency, "random" simulates the genotype from binomial distribution; "fixed" uses the genotype expectation; "Best guess" uses the genotype with highest probability. - `MinP.compare`: Whether to compare with the GEE based minimum p-value (MinP) test. The default is FALSE. Please note that implementing the GEE based MinP test is time consuming. - `...`: Other options of the GEE based MinP test. Defined same as in function ``test.MinP". ## Returns - **results**: First column contains the set ID; Second column contains the p-values; Third column contains the number of tested SNPs. ## Examples ```r # * Since the Plink data files used here are hard to be included in a R package, # The usage is marked by "#" to pass the package check. #library(LGRF) ############################################## # Plink data files: File.Bed, File.Bim, File.Fam # Files defining the sets: File.SetID, File.SSD, File.Info # For longitudinal data, outcome and covariates are saved in a separate file: Y, time, X. # Null model was fitted using function null.LGRF. # Create the MW File # File.Bed<-"./example.bed" # File.Bim<-"./example.bim" # File.Fam<-"./example.fam" # File.SetID<-"./example.SetID" # File.SSD<-"./example.SSD" # File.Info<-"./example.SSD.info" # Generate SSD file # To use binary ped files, you have to generate SSD file first. # If you already have a SSD file, you do not need to call this function. # Generate_SSD_SetID(File.Bed, File.Bim, File.Fam, File.SetID, File.SSD, File.Info) # SSD.INFO<-Open_SSD(File.SSD, File.Info) # Number of samples # SSD.INFO$nSample # Number of Sets # SSD.INFO$nSets ## Fit the null model # Y: outcomes, n by 1 matrix where n is the total number of observations # X: covariates, n by p matrix # time: describe longitudinal structure, n by 2 matrix # result.null<-null.LGRF(Y,time,X=cbind(X,time[,2])) # *Please note that the second column of time should be included as a covairate if # the gene by time interaction effect will be incorperated. ## Test all regions # out_all<-LGRF.SSD.All(SSD.INFO, result.null) # Example result # out.all$results # SetID P.value N.Marker # 1 GENE_01 0.6568851 94 # 2 GENE_02 0.1822183 84 # 3 GENE_03 0.3836986 108 # 4 GENE_04 0.1265337 101 # 5 GENE_05 0.3236089 103 # 6 GENE_06 0.9401741 94 # 7 GENE_07 0.1043820 104 # 8 GENE_08 0.6093275 96 # 9 GENE_09 0.6351147 100 # 10 GENE_10 0.5631549 100 ## Test all regions, and compare with GEE based MinP test # out_all<-LGRF.SSD.All(SSD.INFO, result.null,MinP.compare=T) # Example result # out.all$results # SetID P.value P.value.MinP N.Marker # 1 GENE_01 0.62842 1.0000 94 # 2 GENE_02 0.06558 0.2718 84 # 3 GENE_03 0.61795 1.0000 108 # 4 GENE_04 0.39667 0.7052 101 # 5 GENE_05 0.17371 0.5214 103 # 6 GENE_06 0.90104 1.0000 94 # 7 GENE_07 0.10143 0.1188 104 # 8 GENE_08 0.78082 0.3835 96 # 9 GENE_09 0.21966 0.5364 100 # 10 GENE_10 0.25468 0.3527 100 ```

LGRF.SSD.All function