@@ -47,10 +47,10 @@ Z <- prepareTensorfromList(Multi,10)

 Z <- aperm(Z,c(2,1,3))

 require(RTCGA.clinical)

 Clinical <- list(BLCA.clinical,BRCA.clinical,CESC.clinical,COAD.clinical)

-Multi_sample <- list(BLCA.rnaseq[seq_len(100),1,drop=F],

-              BRCA.rnaseq[seq_len(100),1,drop=F],

-              CESC.rnaseq[seq_len(100),1,drop=F],

-              COAD.rnaseq[seq_len(100),1,drop=F])

+Multi_sample <- list(BLCA.rnaseq[seq_len(100),1,drop=FALSE],

+              BRCA.rnaseq[seq_len(100),1,drop=FALSE],

+              CESC.rnaseq[seq_len(100),1,drop=FALSE],

+              COAD.rnaseq[seq_len(100),1,drop=FALSE])

 #patient.stage_event.tnm_categories.pathologic_categories.pathologic_m

 k <- c(770,1482,773,791)

 #patient.bcr_patient_barcode

@@ -63,7 +63,8 @@ HOSVD <- computeHosvd(Z)

 cond<- attr(Z,"sampleData")

 index <- selectFeatureProj(HOSVD,Multi,cond,de=1e-3,input_all=3) #Batch mode

 head(tableFeatures(Z,index))

-genes <-unlist(lapply(strsplit(tableFeatures(Z,index)[,1],"|",fixed=T),"[",1))

+genes <-unlist(lapply(strsplit(tableFeatures(Z,index)[,1],"|",

+                               fixed=TRUE),"[",1))

 ```

 # Enrichr 

@@ -86,7 +86,7 @@ input_all <- selectSingularValueVectorLarge(HOSVD,cond,input_all=c(12,1))

 Finally,  we perform the following function to select features in individual 

 omics profiles in an interative mode

 ```

-HOSVD$U[[1]] <- HOSVD$U[[2]] #selectFeatureSquareのHOSVD$U[[1]]を[[2]]にすればこれは不要

+

 index_all <- selectFeatureSquare(HOSVD,input_all,CLL_data,

                                  de=c(0.5,0.1,0.1,1))

 ```