R version 4.5.0 RC (2025-04-04 r88113 ucrt) -- "How About a Twenty-Six"
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Platform: x86_64-w64-mingw32/x64

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> library(plasma)
> fls <- try(loadESCAdata())
> if (inherits(fls, "try-error")) {
+   stop("Unable to load data from remote server.")
+ }
> ls()
[1] "fls"
> ## prepare MultiOmics
> MO <- with(plasmaEnv, prepareMultiOmics(assemble, Outcome) )
> MO <- MO[c("ClinicalBin", "ClinicalCont", "RPPA"),]
> summary(MO)
Datasets:
     ClinicalBin ClinicalCont RPPA
[1,]          53            6  192
[2,]         185          185  185
Outcomes:
   patient_id  vital_status days_to_death    days_to_last_followup
 a3i8   :  1   alive:108    Min.   :   9.0   Min.   :   4.0       
 a3ql   :  1   dead : 77    1st Qu.: 180.0   1st Qu.: 336.5       
 a3y9   :  1                Median : 351.0   Median : 402.5       
 a3ya   :  1                Mean   : 495.2   Mean   : 570.1       
 a3yb   :  1                3rd Qu.: 650.0   3rd Qu.: 696.8       
 a3yc   :  1                Max.   :2532.0   Max.   :3714.0       
 (Other):179                NA's   :108      NA's   :77           
      Days       
 Min.   :   4.0  
 1st Qu.: 232.0  
 Median : 400.0  
 Mean   : 538.9  
 3rd Qu.: 681.0  
 Max.   :3714.0  
                 
> ## split into train and test
> set.seed(12345)
> train <- rep(FALSE, 185)
> train[sample(185, 113)] <- TRUE
> MO2 <- MO[, train]
> summary(MO2)
Datasets:
     ClinicalBin ClinicalCont RPPA
[1,]          53            6  192
[2,]         113          113  113
Outcomes:
   patient_id  vital_status days_to_death    days_to_last_followup
 a3ql   :  1   alive:64     Min.   :   9.0   Min.   :  11.0       
 a3y9   :  1   dead :49     1st Qu.: 157.0   1st Qu.: 318.8       
 a3ya   :  1                Median : 351.0   Median : 404.5       
 a3yc   :  1                Mean   : 494.6   Mean   : 572.7       
 a43c   :  1                3rd Qu.: 600.0   3rd Qu.: 652.8       
 a43h   :  1                Max.   :2532.0   Max.   :3714.0       
 (Other):107                NA's   :64       NA's   :49           
      Days       
 Min.   :   9.0  
 1st Qu.: 238.0  
 Median : 400.0  
 Mean   : 538.8  
 3rd Qu.: 632.0  
 Max.   :3714.0  
                 
> ## test complete cox models
> bigfit <- fitCoxModels(MO2, "Days", "vital_status", "dead")
Fitting model with  ClinicalBin 
____************************************************____
____There are some NAs in X but not in Y____
____Component____ 1 ____
____Component____ 2 ____
____Component____ 3 ____
____Predicting X with NA in X and not in Y____
****________________________________________________****

Fitting model with  ClinicalCont 
____************************************************____
____There are some NAs in X but not in Y____
____Component____ 1 ____
____Component____ 2 ____
____Predicting X with NA in X and not in Y____
****________________________________________________****

Fitting model with  RPPA 
____************************************************____
____Component____ 1 ____
____Component____ 2 ____
____Component____ 3 ____
____Predicting X without NA neither in X nor in Y____
****________________________________________________****

Warning messages:
1: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights,  :
  Loglik converged before variable  1 ; coefficient may be infinite. 
2: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights,  :
  Loglik converged before variable  1,2 ; coefficient may be infinite. 
3: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights,  :
  Loglik converged before variable  1,2,3 ; coefficient may be infinite. 
> ## extend across dataset pairs
> mfm <- plasma(MO2, bigfit)
ClinicalBin 
ClinicalCont 
RPPA 
ClinicalBin 
	 ClinicalBin 
	 ClinicalCont 
	 RPPA 
ClinicalCont 
	 ClinicalBin 
	 ClinicalCont 
	 RPPA 
RPPA 
	 ClinicalBin 
	 ClinicalCont 
	 RPPA 
> plot(mfm)
> 
> cross <- getCompositeWeights(mfm, "ClinicalBin", "RPPA")
> summary(cross)
Contributions of dataset ClinicalBin to components from RPPA .
     RPPA1               RPPA2               RPPA3           
 Min.   :-1.152419   Min.   :-1.228502   Min.   :-0.2181669  
 1st Qu.:-0.147531   1st Qu.:-0.136706   1st Qu.:-0.0293259  
 Median : 0.000000   Median : 0.000000   Median : 0.0000000  
 Mean   :-0.009063   Mean   :-0.006883   Mean   :-0.0006515  
 3rd Qu.: 0.172013   3rd Qu.: 0.230221   3rd Qu.: 0.0472324  
 Max.   : 0.853180   Max.   : 0.952361   Max.   : 0.1737181  
> image(cross)
> 
> heat(cross)
> 
> cb <- getAllWeights(mfm, "ClinicalBin")
> summary(cb)
Contributions of dataset ClinicalBin to components from all datasets.
  ClinicalBin1        ClinicalBin2         ClinicalBin3       
 Min.   :-0.717541   Min.   :-6.338e-02   Min.   :-0.5266625  
 1st Qu.:-0.109651   1st Qu.:-1.037e-02   1st Qu.:-0.0636025  
 Median : 0.027175   Median : 0.000e+00   Median : 0.0000000  
 Mean   : 0.001669   Mean   : 3.054e-05   Mean   : 0.0004748  
 3rd Qu.: 0.101408   3rd Qu.: 1.336e-02   3rd Qu.: 0.0636025  
 Max.   : 0.717541   Max.   : 7.376e-02   Max.   : 0.5640754  
 ClinicalCont1       ClinicalCont2          RPPA1               RPPA2          
 Min.   :-0.441024   Min.   :-0.85249   Min.   :-1.152419   Min.   :-1.228502  
 1st Qu.:-0.097656   1st Qu.:-0.17343   1st Qu.:-0.147531   1st Qu.:-0.136706  
 Median : 0.000000   Median : 0.00000   Median : 0.000000   Median : 0.000000  
 Mean   :-0.003019   Mean   : 0.02688   Mean   :-0.009063   Mean   :-0.006883  
 3rd Qu.: 0.053342   3rd Qu.: 0.14757   3rd Qu.: 0.172013   3rd Qu.: 0.230221  
 Max.   : 0.380172   Max.   : 1.12999   Max.   : 0.853180   Max.   : 0.952361  
     RPPA3           
 Min.   :-0.2181669  
 1st Qu.:-0.0293259  
 Median : 0.0000000  
 Mean   :-0.0006515  
 3rd Qu.: 0.0472324  
 Max.   : 0.1737181  
> image(cb)
> heat(cb)
> getTop(cb)
$ClinicalBin1
character(0)

$ClinicalBin2
[1] "esophageal_tumor_involvement_site.mid"

$ClinicalBin3
character(0)

$ClinicalCont1
[1] "pathology_N_stage.n0"

$ClinicalCont2
[1] "neoplasm_histologic_grade.g3"

$RPPA1
[1] "tobacco.NeverSmoker"

$RPPA2
[1] "neoplasm_histologic_grade.g3"

$RPPA3
[1] "neoplasm_histologic_grade.g3"

> 
> rppaContrib <- getAllWeights(mfm, "RPPA")
> getTop(rppaContrib, 5)
     ClinicalBin1      ClinicalBin2          ClinicalBin3      ClinicalCont1   
[1,] "SERPINE1.PAI.1"  "CDH1.E.Cadherin"     "CLDN7.Claudin.7" "SERPINE1.PAI.1"
[2,] "CDH1.E.Cadherin" "SERPINE1.PAI.1"      "C12ORF5.TIGAR"   "TFRC.TFRC"     
[3,] "SRC.Src_pY527"   "SRC.Src_pY527"       "CDKN1A.p21"      "C12ORF5.TIGAR" 
[4,] "C12ORF5.TIGAR"   "CTNNB2.beta.Catenin" "SERPINE1.PAI.1"  "SRC.Src_pY527" 
[5,] "PDCD4.PDCD4"     "STAT5A.STAT5.alpha"  "EIF4G1.eIF4G"    "PDCD4.PDCD4"   
     ClinicalCont2     RPPA1                 RPPA2                
[1,] "VHL.VHL"         "CDH1.E.Cadherin"     "CDH1.E.Cadherin"    
[2,] "EIF4G1.eIF4G"    "SERPINE1.PAI.1"      "RICTOR.Rictor"      
[3,] "CDH1.E.Cadherin" "RICTOR.Rictor"       "MYH11.MYH11"        
[4,] "TFRC.TFRC"       "CTNNB2.beta.Catenin" "RBM15.RBM15"        
[5,] "CCNB1.Cyclin_B1" "MYH11.MYH11"         "CTNNB2.beta.Catenin"
     RPPA3              
[1,] "RICTOR.Rictor"    
[2,] "MYH11.MYH11"      
[3,] "TFRC.TFRC"        
[4,] "SERPINE1.PAI.1"   
[5,] "NDRG1.NDRG1_pT346"
> image(rppaContrib)
> heat(rppaContrib)
> 
> Q <- max(abs(quantile(rppaContrib@contrib, c(0.05, 0.95))))
> sig <- apply(abs(rppaContrib@contrib) > Q, 1, any)
> smaller <- rppaContrib[sig,]
> image(smaller)
> heat(smaller)
> 
> proc.time()
   user  system elapsed 
  10.09    1.29   12.79