David Gomez-Cabrero
| Snapshot Date: 2026-05-19 13:40 -0400 (Tue, 19 May 2026) |
| git_url: https://git.bioconductor.org/packages/STATegRa |
| git_branch: RELEASE_3_23 |
| git_last_commit: e70783e |
| git_last_commit_date: 2026-04-28 08:40:02 -0400 (Tue, 28 Apr 2026) |
| Back to Build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-05-20 11:32 -0400 (Wed, 20 May 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 RC (2026-04-17 r89917) -- "Because it was There" | 4995 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 2190/2418 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| STATegRa 1.48.0 (landing page) David Gomez-Cabrero
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||||
| See other builds for STATegRa in R Universe. | ||||||||||||||
|
To the developers/maintainers of the STATegRa package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/STATegRa.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: STATegRa |
| Version: 1.48.0 |
| Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:STATegRa.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings STATegRa_1.48.0.tar.gz |
| StartedAt: 2026-05-20 05:37:41 -0400 (Wed, 20 May 2026) |
| EndedAt: 2026-05-20 05:42:35 -0400 (Wed, 20 May 2026) |
| EllapsedTime: 294.3 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: STATegRa.Rcheck |
| Warnings: 0 |
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### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:STATegRa.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings STATegRa_1.48.0.tar.gz
###
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* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/STATegRa.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-05-20 09:37:41 UTC
* checking for file ‘STATegRa/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘STATegRa’ version ‘1.48.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘STATegRa’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... NOTE
modelSelection,list-numeric-character: no visible binding for global
variable ‘components’
modelSelection,list-numeric-character: no visible binding for global
variable ‘mylabel’
plotVAF,caClass: no visible binding for global variable ‘comp’
plotVAF,caClass: no visible binding for global variable ‘VAF’
plotVAF,caClass: no visible binding for global variable ‘block’
selectCommonComps,list-numeric: no visible binding for global variable
‘comps’
selectCommonComps,list-numeric: no visible binding for global variable
‘block’
selectCommonComps,list-numeric: no visible binding for global variable
‘comp’
selectCommonComps,list-numeric: no visible binding for global variable
‘ratio’
Undefined global functions or variables:
VAF block comp components comps mylabel ratio
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Found the following Rd file(s) with Rd \link{} targets missing package
anchors:
modelSelection.Rd: ggplot
Please provide package anchors for all Rd \link{} targets not in the
package itself and the base packages.
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
plotRes 5.267 0.07 5.337
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘STATEgRa_Example.omicsCLUST.R’
Running ‘STATEgRa_Example.omicsPCA.R’
Running ‘STATegRa_Example.omicsNPC.R’
Running ‘runTests.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.23-bioc/meat/STATegRa.Rcheck/00check.log’
for details.
STATegRa.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL STATegRa ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’ * installing *source* package ‘STATegRa’ ... ** this is package ‘STATegRa’ version ‘1.48.0’ ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (STATegRa)
STATegRa.Rcheck/tests/runTests.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> BiocGenerics:::testPackage("STATegRa")
Common components
[1] 2
Distinctive components
[[1]]
[1] 0
[[2]]
[1] 0
Common components
[1] 2
Distinctive components
[[1]]
[1] 1
[[2]]
[1] 1
Common components
[1] 2
Distinctive components
[[1]]
[1] 2
[[2]]
[1] 2
RUNIT TEST PROTOCOL -- Wed May 20 05:40:43 2026
***********************************************
Number of test functions: 4
Number of errors: 0
Number of failures: 0
1 Test Suite :
STATegRa RUnit Tests - 4 test functions, 0 errors, 0 failures
Number of test functions: 4
Number of errors: 0
Number of failures: 0
Warning messages:
1: In rownames(pData) == colnames(exprs) :
longer object length is not a multiple of shorter object length
2: In modelSelection(Input = list(B1, B2), Rmax = 4, fac.sel = "%accum", :
Rmax cannot be higher than the minimum of components selected for each block. Rmax fixed to: 2
3: In modelSelection(Input = list(B1, B2), Rmax = 4, fac.sel = "fixed.num", :
Rmax cannot be higher than the minimum of components selected for each block. Rmax fixed to: 3
>
> proc.time()
user system elapsed
3.078 0.167 3.232
STATegRa.Rcheck/tests/STATEgRa_Example.omicsCLUST.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> ###########################################
> ########### EXAMPLE OF THE OMICSCLUSTERING
> ###########################################
> require(STATegRa)
Loading required package: STATegRa
>
> #############################################
> ## PART 1: CREATING a bioMap CLASS
> #############################################
> ####### This part creates or reads the map between features.
> ####### In the present example the map is downloaded from a resource.
> ####### then the class is created.
>
> #load("../data/STATegRa_S2.rda")
> data(STATegRa_S2)
>
> MAP.SYMBOL<-bioMap(name = "Symbol-miRNA",
+ metadata = list(type_v1="Gene",type_v2="miRNA",
+ source_database="targetscan.Hs.eg.db",
+ data_extraction="July2014"),
+ map=mapdata)
>
>
> #############################################
> ## PART 2: CREATING a bioDist CLASS
> #############################################
> ##### In the second part given a set of main features and surrogate feautres,
> ##### the profile of the main features is computed through the surrogate features.
>
> # Load Data
> data(STATegRa_S1)
> #load("../data/STATegRa.S1.Rdata")
>
> ## Create ExpressionSets
> # source("../R/STATegRa_omicsPCA_classes_and_methods.R")
> # Block1 - Expression data
> mRNA.ds <- createOmicsExpressionSet(Data=Block1,pData=ed,pDataDescr=c("classname"))
> # Block2 - miRNA expression data
> miRNA.ds <- createOmicsExpressionSet(Data=Block2,pData=ed,pDataDescr=c("classname"))
>
> # Create Gene-gene distance computed through miRNA data
> bioDistmiRNA<-bioDist(referenceFeatures = rownames(Block1),
+ reference = "Var1",
+ mapping = MAP.SYMBOL,
+ surrogateData = miRNA.ds, ### miRNA data
+ referenceData = mRNA.ds, ### mRNA data
+ maxitems=2,
+ selectionRule="sd",
+ expfac=NULL,
+ aggregation = "sum",
+ distance = "spearman",
+ noMappingDist = 0,
+ filtering = NULL,
+ name = "mRNAbymiRNA")
>
> require(Biobase)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: generics
Attaching package: 'generics'
The following objects are masked from 'package:base':
as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
setequal, union
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:stats':
IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
as.data.frame, basename, cbind, colnames, dirname, do.call,
duplicated, eval, evalq, get, grep, grepl, is.unsorted, lapply,
mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
rank, rbind, rownames, sapply, saveRDS, table, tapply, unique,
unsplit, which.max, which.min
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
>
> # Create Gene-gene distance through mRNA data
> bioDistmRNA<-bioDistclass(name = "mRNAbymRNA",
+ distance = cor(t(exprs(mRNA.ds)),method="spearman"),
+ map.name = "id",
+ map.metadata = list(),
+ params = list())
>
> #############################################
> ## PART 3: CREATING a LISTOF WEIGTHED DISTANCES MATRICES: bioDistWList
> #############################################
>
> bioDistList<-list(bioDistmRNA,bioDistmiRNA)
> weights<-matrix(0,4,2)
> weights[,1]<-c(0,0.33,0.67,1)
> weights[,2]<-c(1,0.67,0.33,0)#
>
> bioDistWList<-bioDistW(referenceFeatures = rownames(Block1),
+ bioDistList = bioDistList,
+ weights=weights)
> length(bioDistWList)
[1] 4
>
> #############################################
> ## PART 4: DEFINING THE STRENGTH OF ASSOCIATIONS IN GENERAL
> #############################################
>
> bioDistWPlot(referenceFeatures = rownames(Block1) ,
+ listDistW = bioDistWList,
+ method.cor="spearman")
Warning messages:
1: In cor.test.default(getDist(listDistW[[i]])[referenceFeatures, referenceFeatures], :
cannot compute exact p-value with ties
2: In cor.test.default(getDist(listDistW[[i]])[referenceFeatures, referenceFeatures], :
cannot compute exact p-value with ties
3: In cor.test.default(getDist(listDistW[[i]])[referenceFeatures, referenceFeatures], :
cannot compute exact p-value with ties
4: In plot.window(...) :
axis(2, *): range of values ( 0) is small wrt |M| = 3e-09 --> not pretty()
5: In plot.window(...) :
axis(2, *): range of values ( 0) is small wrt |M| = 3e-09 --> not pretty()
6: In plot.window(...) :
axis(2, *): range of values ( 0) is small wrt |M| = 3e-09 --> not pretty()
7: In plot.window(...) :
axis(2, *): range of values ( 0) is small wrt |M| = 3e-09 --> not pretty()
>
> #############################################
> ## PART 5: DEFINING THE ASSOCIATIONS FOR A GIVEN GENE
> #############################################
>
> ## IDH1
>
> IDH1.F<-bioDistFeature(Feature = "IDH1" ,
+ listDistW = bioDistWList,
+ threshold.cor=0.7)
> bioDistFeaturePlot(data=IDH1.F)
>
> ## PDGFRA
>
> #PDGFRA.F<-bioDistFeature(Feature = "PDGFRA" ,
> # listDistW = bioDistWList,
> # threshold.cor=0.7)
> #bioDistFeaturePlot(data=PDGFRA.F,name="../vignettes/PDGFRA.png")
>
> ## EGFR
> #EGFR.F<-bioDistFeature(Feature = "EGFR" ,
> # listDistW = bioDistWList,
> # threshold.cor=0.7)
> #bioDistFeaturePlot(data=EGFR.F,name="../vignettes/EGFR.png")
>
> ## MGMT
> #MGMT.F<-bioDistFeature(Feature = "MGMT" ,
> # listDistW = bioDistWList,
> # threshold.cor=0.5)
> #bioDistFeaturePlot(data=MGMT.F,name="../vignettes/MGMT.png")
>
>
>
>
>
> proc.time()
user system elapsed
22.517 0.823 23.328
STATegRa.Rcheck/tests/STATegRa_Example.omicsNPC.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> rm(list = ls())
> require("STATegRa")
Loading required package: STATegRa
> # Load the data
> data("TCGA_BRCA_Batch_93")
> # Setting dataTypes
> dataTypes <- c("count", "count", "continuous")
> # Setting methods to combine pvalues
> combMethods = c("Fisher", "Liptak", "Tippett")
> # Setting number of permutations
> numPerms = 1000
> # Setting number of cores
> numCores = 1
> # Setting holistOmics to print out the steps that it performs.
> verbose = TRUE
> # Run holistOmics analysis.
> output <- omicsNPC(dataInput = TCGA_BRCA_Data, dataTypes = dataTypes, combMethods = combMethods, numPerms = numPerms, numCores = numCores, verbose = verbose)
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calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
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calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
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calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
calcNormFactors has been renamed to normLibSizes
Compute pseudo p-values based on NULL distributions...
NPC p-values calculation...
>
> proc.time()
user system elapsed
61.533 0.516 62.036
STATegRa.Rcheck/tests/STATEgRa_Example.omicsPCA.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> ###########################################
> ########### EXAMPLE OF THE OMICSPCA
> ###########################################
> require(STATegRa)
Loading required package: STATegRa
>
> # g_legend (not exported by STATegRa any more)
> ## code from https://github.com/hadley/ggplot2/wiki/Share-a-legend-between-two-ggplot2-graphs
> g_legend<-function(a.gplot){
+ tmp <- ggplot_gtable(ggplot_build(a.gplot))
+ leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
+ legend <- tmp$grobs[[leg]]
+ return(legend)}
>
> #########################
> ## PART 1. Load data
>
> ## Load data
> data(STATegRa_S3)
>
> ls()
[1] "Block1.PCA" "Block2.PCA" "ed.PCA" "g_legend"
>
> ## Create ExpressionSets
> # Block1 - Expression data
> B1 <- createOmicsExpressionSet(Data=Block1.PCA,pData=ed.PCA,pDataDescr=c("classname"))
> # Block2 - miRNA expression data
> B2 <- createOmicsExpressionSet(Data=Block2.PCA,pData=ed.PCA,pDataDescr=c("classname"))
>
> #########################
> ## PART 2. Model Selection
>
> require(grid)
Loading required package: grid
> require(gridExtra)
Loading required package: gridExtra
> require(ggplot2)
Loading required package: ggplot2
>
> ## Select the optimal components
> ms <- modelSelection(Input=list(B1,B2),Rmax=4,fac.sel="single%",varthreshold=0.03,center=TRUE,scale=TRUE,weight=TRUE)
Common components
[1] 2
Distinctive components
[[1]]
[1] 2
[[2]]
[1] 2
>
>
> #########################
> ## PART 3. Component Analysis
>
> ## 3.1 Component analysis of the three methods
> discoRes <- omicsCompAnalysis(Input=list(B1,B2),Names=c("expr","mirna"),method="DISCOSCA",Rcommon=2,Rspecific=c(2,2),center=TRUE,
+ scale=TRUE,weight=TRUE)
> jiveRes <- omicsCompAnalysis(Input=list(B1,B2),Names=c("expr","mirna"),method="JIVE",Rcommon=2,Rspecific=c(2,2),center=TRUE,
+ scale=TRUE,weight=TRUE)
> o2plsRes <- omicsCompAnalysis(Input=list(B1,B2),Names=c("expr","mirna"),method="O2PLS",Rcommon=2,Rspecific=c(2,2),center=TRUE,
+ scale=TRUE,weight=TRUE)
>
> ## 3.2 Exploring scores structures
>
> # Exploring DISCO-SCA scores structure
> discoRes@scores$common ## Common scores
1 2
sample1 -0.0781574334 0.0431502527
sample2 0.1192218441 -0.0294088003
sample3 0.0531412083 0.0746839790
sample4 -0.0292975127 0.0005960654
sample5 -0.0202091777 -0.0110463533
sample6 -0.1226089046 -0.1053467353
sample7 -0.1078928136 0.0322475254
sample8 -0.1782895251 -0.1449363773
sample9 -0.0468698133 0.0455174383
sample10 0.0036030513 -0.0420110648
sample11 0.0035566459 0.0566292602
sample12 -0.1006128904 -0.0641380948
sample13 0.1174408408 -0.0907488350
sample14 -0.0981203255 -0.0617738397
sample15 -0.0085334341 0.0087013034
sample16 -0.0783148643 -0.1581294814
sample17 0.1483609936 -0.0638581970
sample18 0.0963086247 -0.0556640638
sample19 0.0217244070 0.0720086584
sample20 0.0635636387 0.0779652769
sample21 0.0201840358 -0.1566391216
sample22 -0.0218268771 0.0764103962
sample23 -0.0852042004 0.0032689490
sample24 0.1287170752 -0.1924542642
sample25 0.0430574159 0.0456566754
sample26 0.1453896885 -0.0541511788
sample27 0.0197488761 0.1185656290
sample28 0.1025336343 -0.0650685324
sample29 -0.0706018519 0.0682987624
sample30 0.1295627494 0.0066768518
sample31 -0.1147449117 -0.1232687013
sample32 0.0374310843 -0.0380178524
sample33 -0.0599516026 -0.0136867837
sample34 0.0984200801 -0.0375321420
sample35 0.0543098366 0.0378105306
sample36 -0.1403625460 0.0343755170
sample37 -0.0228941918 0.0732844960
sample38 0.0222077229 0.0962594538
sample39 0.0941738495 -0.0215199031
sample40 -0.0643801193 0.0687869718
sample41 0.0327637995 0.1232188167
sample42 0.0500431838 0.0292473665
sample43 0.0184498793 -0.0233011286
sample44 -0.1487898687 -0.1171353186
sample45 0.1050774212 -0.1123201048
sample46 0.1151195692 0.1094028458
sample47 0.0962593717 0.0288463343
sample48 -0.0004837297 0.0310278728
sample49 -0.1135207747 -0.1213972728
sample50 0.0123553092 0.1740743880
sample51 -0.0550529869 -0.1258886948
sample52 -0.0499121227 -0.0728544697
sample53 -0.1119773646 -0.1588014252
sample54 0.0360055666 -0.0228575631
sample55 -0.0210419015 -0.0006731767
sample56 0.0434169236 -0.0633126032
sample57 -0.0197824602 -0.1150713765
sample58 -0.0030439898 -0.0326098220
sample59 -0.0500253147 -0.0129419582
sample60 -0.0184278666 -0.0136086222
sample61 -0.0150299428 -0.0635026222
sample62 0.0304763870 0.0201318659
sample63 -0.1102252451 -0.1285976939
sample64 -0.1552588072 -0.0971168490
sample65 0.0058503048 -0.0207115314
sample66 0.0025605348 -0.0424319650
sample67 -0.1546634843 0.0661715554
sample68 -0.0536369309 0.0923683225
sample69 -0.0640330382 -0.0081983257
sample70 -0.0163517762 0.0663230013
sample71 0.0102537619 0.1345921647
sample72 0.0654196009 0.0196119058
sample73 0.1048556115 -0.0220938616
sample74 -0.0123799504 -0.0586115288
sample75 -0.0392077963 0.0209754929
sample76 -0.0648953377 0.0524764332
sample77 -0.1172922119 0.0201186734
sample78 0.1463068143 -0.0708472102
sample79 -0.0265211180 0.1603308614
sample80 -0.0279737183 0.0214204908
sample81 -0.0079211497 0.0738451089
sample82 0.1544236518 0.0361467725
sample83 0.0494211361 0.0050047921
sample84 0.0259038459 0.0346549885
sample85 -0.1116484364 0.0031497222
sample86 0.1306483025 0.0377214826
sample87 0.0554778194 0.0459748917
sample88 0.0301623857 -0.0382197577
sample89 0.1016866707 -0.0694034021
sample90 -0.0086819880 0.0201320102
sample91 -0.1578625352 0.2097827814
sample92 -0.0170936807 0.1655807527
sample93 0.0979806816 0.0121512166
sample94 -0.0131484102 0.0114932045
sample95 -0.0315682624 0.0758859350
sample96 -0.0024125617 0.0470135781
sample97 -0.0634545415 -0.0270331785
sample98 0.0359374627 0.0135488349
sample99 0.1009163356 -0.1124779812
sample100 -0.0551753121 -0.0246489678
sample101 0.0080118890 0.1627368634
sample102 0.0046444336 -0.0095631319
sample103 0.0472523166 0.0940393271
sample104 -0.0198159483 0.0591091831
sample105 0.0400237791 0.0160912188
sample106 0.0923808428 -0.0369017687
sample107 0.1019373942 -0.0224954214
sample108 0.0877091655 0.0128834243
sample109 -0.0864824364 0.0900942156
sample110 0.1223115547 0.0096085773
sample111 -0.0257354631 0.0936169520
sample112 0.0765286600 -0.0270347654
sample113 -0.0258803240 -0.0377497000
sample114 -0.0021138930 0.0882014962
sample115 -0.0303460179 0.0723586096
sample116 -0.0780508395 0.0685066568
sample117 -0.0536898095 0.0911908766
sample118 -0.0666651134 0.0236231084
sample119 -0.1021871621 0.2324936917
sample120 -0.0750216545 -0.0243379087
sample121 0.0756936406 -0.0942950659
sample122 0.0259628089 -0.0731986966
sample123 0.1037846252 0.0369197162
sample124 -0.0611207909 -0.0421723486
sample125 0.0738472709 -0.0066950077
sample126 -0.0972916443 -0.0762640213
sample127 -0.0824697629 0.0096637272
sample128 0.1249407668 -0.0929312567
sample129 0.0734067508 0.0434362771
sample130 0.0003502002 0.0309852665
sample131 -0.0930182812 -0.0155937244
sample132 -0.0736222802 -0.0733029693
sample133 0.0498397969 0.0462437562
sample134 -0.1644873484 -0.0720005741
sample135 0.0752297194 -0.0003817887
sample136 -0.0227145783 0.0495505909
sample137 -0.0564717417 0.0288915573
sample138 -0.0255988106 0.0610857214
sample139 -0.0621217799 -0.0235807838
sample140 0.0604152520 0.0435593116
sample141 -0.0246743973 -0.0532648614
sample142 0.0409560331 -0.0316279697
sample143 0.0077355217 0.0476896359
sample144 -0.0173240835 0.0156777999
sample145 -0.0485474508 -0.1202770463
sample146 -0.0419645641 0.0811281162
sample147 0.0977308345 0.0274839856
sample148 -0.0368256189 -0.0803979582
sample149 0.0072865792 0.1532986086
sample150 -0.1020825285 -0.0624774769
sample151 -0.0305399064 0.0289278369
sample152 0.0533594807 0.0638309141
sample153 0.0891627704 -0.1799578091
sample154 0.0727557466 0.0834160808
sample155 0.0880668548 0.0220819493
sample156 0.0276561030 0.0326625300
sample157 0.1155032192 -0.0183616159
sample158 0.0281507508 0.0104938620
sample159 -0.0663235700 -0.0443837279
sample160 0.0302643872 -0.0404265483
sample161 -0.0114715561 0.0591025630
sample162 0.1337087147 -0.1398135523
sample163 -0.1330124459 -0.1688781291
sample164 0.0150336088 -0.0028416018
sample165 -0.0076520286 0.0164128518
sample166 -0.0367794358 -0.0630661947
sample167 -0.1111988867 -0.0030057891
sample168 0.0672981608 -0.0446279288
sample169 0.0413004966 -0.0224394396
> discoRes@scores$dist[[1]] ## Distinctive scores for Block 1
1 2
sample1 -0.0420514610 0.0867863104
sample2 -0.0820828671 -0.0410978002
sample3 0.0155899992 -0.0195182383
sample4 -0.1001337126 -0.0410786643
sample5 -0.0153465988 -0.0253259670
sample6 0.0340325574 -0.0408223201
sample7 0.0722579831 0.0002332209
sample8 -0.0457500333 -0.0370016197
sample9 -0.0086249164 0.0820184907
sample10 -0.0423598689 -0.0083923259
sample11 0.0022548765 0.0787766041
sample12 0.0322105690 0.1479824679
sample13 -0.0293890055 -0.0306748608
sample14 0.0337482516 -0.0367506866
sample15 0.0815539189 0.1275622461
sample16 0.0508451857 0.0540604650
sample17 0.0062596570 0.0041023716
sample18 0.0705639700 -0.0351047713
sample19 -0.0476841539 -0.0509598074
sample20 0.0522962989 0.0715521836
sample21 -0.0119127008 -0.0376093070
sample22 0.0724393278 -0.0095625147
sample23 -0.0992532136 0.0134288828
sample24 -0.1595118537 0.0728662085
sample25 -0.0920693283 -0.0749757238
sample26 -0.0595540205 0.0848966062
sample27 0.0826485901 -0.0086735463
sample28 -0.0384788319 0.0440966891
sample29 0.0777671709 0.1735308483
sample30 0.1229471292 -0.0819005564
sample31 0.0579846122 -0.0238644765
sample32 0.0970393110 -0.0111426327
sample33 0.1017587976 -0.0630442602
sample34 0.0637922821 0.0377941693
sample35 0.0789984499 -0.0229723250
sample36 0.1224939287 -0.1274954982
sample37 0.1798820838 -0.1673427492
sample38 0.0466304690 0.0888160921
sample39 -0.0168687663 0.0421533762
sample40 0.1756392157 -0.1526642417
sample41 0.0042371010 0.0004928792
sample42 -0.0447849661 -0.0651504995
sample43 0.0482308408 -0.0253529282
sample44 -0.1986715021 -0.0545777801
sample45 -0.0741836614 0.0054703314
sample46 0.0478772304 -0.0007072042
sample47 0.0608188571 0.0481622615
sample48 -0.1381489354 0.0578287816
sample49 -0.0530520647 -0.1405532810
sample50 -0.0173799522 0.1602389664
sample51 0.0462560870 0.0303473836
sample52 0.0280064954 0.0280388396
sample53 0.0667621204 0.0237702033
sample54 0.0121833534 -0.0521354322
sample55 0.0182395940 0.0221328433
sample56 -0.0001255628 0.0030907365
sample57 0.0316675345 0.0530190285
sample58 0.0393918124 -0.0297798755
sample59 0.1278290884 -0.0546527989
sample60 0.1486985089 0.1069156516
sample61 0.0793122451 0.0569796510
sample62 0.1172801035 -0.0149198525
sample63 -0.0028726897 0.1300519842
sample64 0.0237364587 0.1073287718
sample65 -0.0126534900 0.0589808445
sample66 -0.0468194822 -0.0771072674
sample67 0.1494264603 -0.0769860341
sample68 0.0977961273 -0.0577351086
sample69 0.0403087293 0.0156042105
sample70 0.0221531336 0.0315440945
sample71 -0.0546434477 -0.0272396430
sample72 0.1107487815 -0.0537319407
sample73 0.0906761254 0.0579966583
sample74 0.0586555379 0.0121421665
sample75 0.0390493311 0.0349282804
sample76 -0.0022960724 -0.1676558798
sample77 -0.0232096262 -0.2067302793
sample78 -0.0929755039 -0.0434939462
sample79 -0.1619496687 -0.0378114196
sample80 0.0680365586 0.1424663478
sample81 -0.0530784020 -0.0358350835
sample82 0.0266821947 -0.0577445122
sample83 0.1517235195 -0.0448554384
sample84 -0.0570967070 -0.0273813221
sample85 0.1086289666 -0.1228119364
sample86 0.0833859940 -0.0442915015
sample87 0.0022018420 -0.0943906858
sample88 -0.0078224950 -0.1140506528
sample89 0.0611057214 -0.0094585166
sample90 0.0022928090 -0.0936253996
sample91 0.0433590661 0.3205982760
sample92 -0.1815335438 -0.0334680246
sample93 0.0267630769 0.0614429016
sample94 0.0181877783 0.0605090401
sample95 -0.0720375678 -0.0013045635
sample96 -0.0559714753 -0.0118791400
sample97 -0.0217411027 0.0195414155
sample98 0.0379177413 0.0588357094
sample99 -0.0792427366 -0.0151273773
sample100 0.0222116393 -0.0023321441
sample101 -0.0387228505 0.1224226220
sample102 -0.2094614172 -0.0516442548
sample103 0.0138481272 0.0301051945
sample104 -0.0807986984 -0.0162718892
sample105 -0.0520493344 -0.1229665146
sample106 -0.0192613321 -0.0185238179
sample107 0.0319017156 0.0405123279
sample108 -0.0140690987 0.0163421384
sample109 -0.1831930066 0.0613007617
sample110 -0.0292790599 -0.0199849075
sample111 -0.1423251969 0.0327340374
sample112 0.0426332840 -0.0029083454
sample113 -0.0771904532 0.0268733678
sample114 -0.0241641383 -0.0184080411
sample115 -0.1959015556 0.0460130741
sample116 -0.1394475993 -0.0530805768
sample117 -0.1672361774 -0.1386536348
sample118 -0.0448344289 -0.0117621922
sample119 -0.0910386231 0.2217433398
sample120 -0.0331392241 -0.0057274484
sample121 0.0307574842 0.1392506538
sample122 -0.0839781198 -0.0291994385
sample123 0.0239650423 -0.0642163737
sample124 -0.0909150657 0.0130419535
sample125 -0.0065350865 -0.1092631810
sample126 0.0935311811 0.1368284019
sample127 0.0035387896 0.0292755634
sample128 -0.0660295531 0.1018566350
sample129 0.0693638605 -0.0695421767
sample130 0.0008493447 -0.0669704330
sample131 0.0431023998 0.0174064853
sample132 -0.0637040165 0.0029374751
sample133 -0.0289494739 -0.0390818822
sample134 0.0446202971 0.0456334495
sample135 0.0712336983 0.0521634929
sample136 0.0596271028 0.0197299298
sample137 0.0793151973 -0.0380628337
sample138 -0.0973548310 -0.0454218230
sample139 0.0539904676 -0.1534327383
sample140 0.0850827053 0.0955814499
sample141 -0.0192681847 -0.0554450055
sample142 -0.0672262025 -0.0461320886
sample143 -0.0303730403 -0.0519260228
sample144 -0.0089364561 0.0145814920
sample145 -0.0638770007 0.0122258443
sample146 0.0585856352 0.0063083322
sample147 0.0894133331 -0.1124615739
sample148 -0.0216366994 -0.0615967109
sample149 -0.0515420636 -0.0839903485
sample150 0.0568283297 -0.0124468939
sample151 -0.0789532375 -0.0261831155
sample152 -0.0330753440 0.1306443591
sample153 -0.1751931379 0.1497732176
sample154 0.0421424376 -0.0037010218
sample155 0.0680177525 0.0095711205
sample156 0.0388911196 0.1057562947
sample157 0.0314769401 0.0561367411
sample158 0.0329620566 0.0353947313
sample159 -0.0398416613 -0.1007373755
sample160 0.0424938747 0.0108496168
sample161 -0.0888371297 -0.0679700141
sample162 -0.0027475999 0.1237843869
sample163 -0.0126105359 0.0725434360
sample164 -0.0566779656 -0.0458324156
sample165 -0.0315336368 -0.0236362333
sample166 -0.0612058186 -0.0425233010
sample167 0.0142729868 0.0179308271
sample168 -0.0169503532 -0.0769617889
sample169 0.0675080339 0.0131505306
> discoRes@scores$dist[[2]] ## Distinctive scores for Block 2
1 2
sample1 -0.0012329669 -1.635717e-01
sample2 -0.0724350071 -6.021272e-03
sample3 -0.0188460443 -1.080036e-01
sample4 0.0390145265 3.114044e-04
sample5 0.1774811635 -2.996385e-02
sample6 -0.0451444415 -3.455859e-02
sample7 -0.0226466246 -7.020149e-03
sample8 -0.1033680241 -9.856800e-03
sample9 0.1350011727 8.979099e-02
sample10 0.1259887246 -5.097853e-02
sample11 0.0979788361 7.086535e-02
sample12 -0.0863019102 -8.620317e-02
sample13 -0.1381401106 1.828007e-01
sample14 -0.0615073855 -2.642803e-02
sample15 0.0381598960 -3.101663e-02
sample16 -0.0048776716 1.271831e-03
sample17 -0.0788480936 -1.547555e-02
sample18 -0.0884188733 -3.795487e-02
sample19 0.0703044410 -1.084004e-01
sample20 -0.0025585522 7.975876e-02
sample21 0.0941601675 -4.126742e-02
sample22 -0.0550273410 -7.806742e-02
sample23 0.0679495286 -4.102006e-02
sample24 -0.1310962800 1.649309e-01
sample25 0.0113585266 -4.426863e-02
sample26 -0.1402945916 2.016541e-02
sample27 0.0261561131 1.588464e-03
sample28 -0.0724198715 5.850591e-02
sample29 -0.0330058576 2.060841e-03
sample30 -0.0228752530 -2.015429e-02
sample31 -0.0635067929 -6.670334e-02
sample32 0.0685099671 -4.955272e-02
sample33 -0.0777765200 -1.272078e-01
sample34 0.0157842430 -3.024314e-02
sample35 -0.0529632751 1.500972e-01
sample36 0.0070900770 2.025307e-01
sample37 -0.0442420574 1.802089e-01
sample38 -0.0781511303 -3.676419e-02
sample39 0.0120331861 -3.388842e-02
sample40 -0.0473292051 1.471562e-01
sample41 0.0228189400 -2.673553e-02
sample42 -0.0245360248 -7.960867e-02
sample43 0.1036362820 -8.229577e-02
sample44 -0.1012228825 7.049449e-02
sample45 0.0013732047 -2.450913e-02
sample46 -0.0558510016 2.947396e-03
sample47 -0.0380481170 4.554174e-02
sample48 0.0784342057 4.888980e-02
sample49 -0.0605163959 -1.162357e-02
sample50 0.0530079243 -2.737931e-02
sample51 0.1514646545 5.678344e-02
sample52 0.1860935240 1.246717e-01
sample53 -0.0064177076 -2.700994e-02
sample54 0.0697038351 -2.308389e-02
sample55 0.1633577033 1.366442e-02
sample56 0.1011485109 4.682205e-02
sample57 0.1730374222 1.609603e-01
sample58 -0.0071384697 -1.666955e-02
sample59 -0.0030461666 3.005286e-02
sample60 0.0215835150 2.665878e-01
sample61 0.1510583651 1.002385e-01
sample62 -0.0925533933 -4.845841e-02
sample63 -0.0596311788 -4.137023e-02
sample64 -0.0449225798 -2.600586e-03
sample65 0.0939383760 -4.406909e-02
sample66 0.1063400755 -5.709993e-02
sample67 -0.0201590011 2.361728e-01
sample68 0.0037203207 2.418391e-02
sample69 -0.0645161201 -1.155622e-01
sample70 -0.1013440017 -1.351789e-01
sample71 -0.0016467898 -2.976841e-02
sample72 0.0328893041 -2.835856e-02
sample73 0.0275080065 -5.148185e-02
sample74 0.1341719702 -7.895280e-02
sample75 0.0951575664 -3.943183e-02
sample76 -0.0864721969 3.034992e-02
sample77 -0.1035749571 -2.545353e-02
sample78 -0.1575644132 4.939592e-02
sample79 0.0189137035 4.874679e-02
sample80 0.1384140587 4.266182e-05
sample81 -0.0118846472 -6.357931e-02
sample82 -0.1675308161 3.533912e-02
sample83 -0.0065673381 -7.812608e-02
sample84 0.1486891603 -3.109057e-02
sample85 -0.0532724410 7.417885e-02
sample86 -0.1138477320 -1.914588e-05
sample87 0.0432863983 6.080473e-02
sample88 0.0433450373 1.402491e-01
sample89 0.0331205802 -1.395401e-02
sample90 -0.0607412811 -8.610414e-02
sample91 -0.0566272682 1.303747e-01
sample92 -0.0359582553 1.061604e-01
sample93 -0.0433646355 -4.443635e-02
sample94 -0.0477291300 -1.059574e-01
sample95 -0.0249595791 -3.980525e-02
sample96 0.0035218999 -9.293928e-02
sample97 -0.0066048753 -1.527231e-01
sample98 0.0020366822 -5.579549e-02
sample99 -0.0886616081 -3.728228e-02
sample100 -0.1091259131 -3.560420e-02
sample101 -0.0739726513 -4.317998e-02
sample102 0.0574461131 -2.783916e-02
sample103 0.0142731013 9.705567e-03
sample104 0.0710395190 4.068351e-02
sample105 0.0980831348 -3.452953e-02
sample106 -0.0254259305 3.628983e-02
sample107 -0.0160653433 -9.173395e-02
sample108 -0.0200987654 -2.379692e-02
sample109 -0.0389780699 1.692358e-02
sample110 -0.0326304844 2.988109e-02
sample111 0.0676937533 -6.038213e-02
sample112 0.0167883447 5.336938e-03
sample113 0.0969217011 -2.757604e-02
sample114 -0.0026398364 -9.209156e-02
sample115 -0.0308047358 1.603822e-02
sample116 -0.1240307210 1.273000e-01
sample117 0.0334729047 5.392710e-02
sample118 -0.1037152934 6.252430e-02
sample119 -0.1064176720 1.196203e-01
sample120 -0.0771355093 -1.004933e-01
sample121 -0.0129350737 3.181975e-02
sample122 0.0847492295 -5.568328e-02
sample123 -0.0041336771 7.693184e-03
sample124 -0.0583458008 -8.396390e-02
sample125 0.0634844612 -5.232540e-02
sample126 -0.0662580934 -1.091733e-01
sample127 -0.0865024609 -1.094176e-01
sample128 -0.0627817424 -1.470965e-02
sample129 -0.0336276439 -4.007858e-02
sample130 -0.0293517746 -8.046117e-02
sample131 -0.0469197665 -2.209747e-03
sample132 -0.0241740677 -1.248598e-01
sample133 0.0907303206 1.466701e-02
sample134 -0.0350842080 7.539662e-02
sample135 0.0001333417 9.185383e-03
sample136 -0.0335876058 -9.860273e-02
sample137 -0.0640148903 -7.554469e-02
sample138 0.0060964824 -1.742762e-02
sample139 -0.0592084451 5.614969e-02
sample140 0.0427985932 -1.099550e-02
sample141 0.0618796394 -9.301038e-02
sample142 0.0898554468 3.573417e-02
sample143 0.0817389204 8.880524e-02
sample144 0.0787754778 -3.821391e-02
sample145 0.1085821580 1.569476e-01
sample146 -0.0589557947 -4.373359e-02
sample147 -0.0495330425 7.277210e-03
sample148 0.1161592801 9.079076e-03
sample149 -0.0121579484 7.788375e-02
sample150 -0.0314512532 3.520212e-02
sample151 0.0575382158 -1.945353e-02
sample152 -0.0494542117 7.025537e-02
sample153 -0.0941332743 2.153297e-01
sample154 -0.0335932012 2.078730e-02
sample155 0.0690457661 -2.780409e-02
sample156 0.1039901621 -6.292524e-02
sample157 -0.0408645772 8.065515e-03
sample158 0.1018105310 7.816880e-03
sample159 -0.0281730536 -1.207207e-02
sample160 0.1643053022 2.978105e-03
sample161 0.0374329231 8.524610e-02
sample162 -0.0804535303 8.349753e-02
sample163 -0.0743227961 -1.406226e-02
sample164 0.1208806010 -2.139460e-02
sample165 0.1608115908 2.025192e-02
sample166 -0.0425944637 -2.660715e-02
sample167 -0.0226849485 -4.464281e-02
sample168 -0.0180735571 -7.466258e-04
sample169 0.0190779018 2.645403e-02
> # Exploring O2PLS scores structure
> o2plsRes@scores$common[[1]] ## Common scores for Block 1
[,1] [,2]
sample1 -0.0572060227 -1.729087e-02
sample2 0.0875245208 1.112588e-02
sample3 0.0403482602 -3.168994e-02
sample4 -0.0218345996 4.052760e-06
sample5 -0.0150905011 4.795041e-03
sample6 -0.0924362933 4.511003e-02
sample7 -0.0793066751 -1.243823e-02
sample8 -0.1342997187 6.215220e-02
sample9 -0.0338886944 -1.854401e-02
sample10 0.0020547173 1.749421e-02
sample11 0.0037275602 -2.364116e-02
sample12 -0.0753094533 2.772698e-02
sample13 0.0856160091 3.679963e-02
sample14 -0.0737457307 2.668452e-02
sample15 -0.0062111746 -3.554864e-03
sample16 -0.0602355268 6.675115e-02
sample17 0.1086768843 2.524534e-02
sample18 0.0702999472 2.231671e-02
sample19 0.0173785882 -3.024846e-02
sample20 0.0484173812 -3.310904e-02
sample21 0.0124657042 6.517144e-02
sample22 -0.0140989936 -3.159137e-02
sample23 -0.0627028403 -5.393710e-04
sample24 0.0919972100 7.909297e-02
sample25 0.0326998483 -1.945206e-02
sample26 0.1064741246 2.120849e-02
sample27 0.0166058995 -4.964993e-02
sample28 0.0743504770 2.614211e-02
sample29 -0.0511008491 -2.782647e-02
sample30 0.0962250842 -3.974893e-03
sample31 -0.0869563008 5.250819e-02
sample32 0.0271858919 1.552005e-02
sample33 -0.0448364581 6.243160e-03
sample34 0.0718415218 1.469396e-02
sample35 0.0403086451 -1.632629e-02
sample36 -0.1036402827 -1.304320e-02
sample37 -0.0159385744 -3.036525e-02
sample38 0.0182198369 -4.034805e-02
sample39 0.0690363619 8.058350e-03
sample40 -0.0467312750 -2.810325e-02
sample41 0.0263674438 -5.171216e-02
sample42 0.0374578960 -1.268634e-02
sample43 0.0132336869 9.536642e-03
sample44 -0.1119154428 5.028683e-02
sample45 0.0759639367 4.587903e-02
sample46 0.0871885519 -4.670385e-02
sample47 0.0721490571 -1.288540e-02
sample48 0.0005086144 -1.290565e-02
sample49 -0.0858177028 5.173760e-02
sample50 0.0118992665 -7.276215e-02
sample51 -0.0426446855 5.306205e-02
sample52 -0.0381605826 3.086785e-02
sample53 -0.0855757630 6.730043e-02
sample54 0.0261723092 9.184260e-03
sample55 -0.0156418304 4.682404e-04
sample56 0.0307831193 2.597550e-02
sample57 -0.0157242103 4.829381e-02
sample58 -0.0031174404 1.359898e-02
sample59 -0.0373001859 5.868397e-03
sample60 -0.0142609099 5.831654e-03
sample61 -0.0122255144 2.663579e-02
sample62 0.0228002942 -8.692265e-03
sample63 -0.0833127581 5.473229e-02
sample64 -0.1166548159 4.196500e-02
sample65 0.0038808902 8.568590e-03
sample66 0.0011561811 1.766612e-02
sample67 -0.1129311062 -2.608702e-02
sample68 -0.0382526429 -3.804045e-02
sample69 -0.0476502440 4.003241e-03
sample70 -0.0110329882 -2.752719e-02
sample71 0.0096850282 -5.627056e-02
sample72 0.0487124704 -8.800131e-03
sample73 0.0773058132 8.239864e-03
sample74 -0.0102488176 2.454957e-02
sample75 -0.0286613976 -8.387293e-03
sample76 -0.0472655595 -2.129315e-02
sample77 -0.0865043074 -7.296820e-03
sample78 0.1070293698 2.818346e-02
sample79 -0.0165060681 -6.659721e-02
sample80 -0.0206765949 -8.712112e-03
sample81 -0.0050943615 -3.079175e-02
sample82 0.1153622361 -1.647054e-02
sample83 0.0367979217 -2.538114e-03
sample84 0.0199463070 -1.468961e-02
sample85 -0.0827122185 -2.709824e-04
sample86 0.0969487314 -1.699897e-02
sample87 0.0421957457 -1.965953e-02
sample88 0.0215934743 1.566050e-02
sample89 0.0751559502 2.811652e-02
sample90 -0.0057328000 -8.283795e-03
sample91 -0.1134005268 -8.603522e-02
sample92 -0.0101689918 -6.894992e-02
sample93 0.0725967502 -6.003176e-03
sample94 -0.0096878852 -4.693081e-03
sample95 -0.0223502239 -3.139636e-02
sample96 -0.0013232863 -1.963604e-02
sample97 -0.0476541710 1.183660e-02
sample98 0.0269546160 -5.978398e-03
sample99 0.0728179461 4.597884e-02
sample100 -0.0413398038 1.079347e-02
sample101 0.0087536994 -6.796076e-02
sample102 0.0032509529 3.932612e-03
sample103 0.0360342395 -3.973263e-02
sample104 -0.0141722563 -2.453107e-02
sample105 0.0294940465 -7.140722e-03
sample106 0.0686472054 1.462895e-02
sample107 0.0748635927 8.401339e-03
sample108 0.0650175850 -6.211942e-03
sample109 -0.0628017242 -3.681224e-02
sample110 0.0905513691 -5.169053e-03
sample111 -0.0176679473 -3.884777e-02
sample112 0.0570870472 1.066018e-02
sample113 -0.0200110554 1.596044e-02
sample114 -0.0001474542 -3.679272e-02
sample115 -0.0213333038 -2.991667e-02
sample116 -0.0567675453 -2.785636e-02
sample117 -0.0379865990 -3.752078e-02
sample118 -0.0484878786 -9.173691e-03
sample119 -0.0713511831 -9.598634e-02
sample120 -0.0555093586 1.089843e-02
sample121 0.0542443861 3.861344e-02
sample122 0.0178575357 3.027138e-02
sample123 0.0775020581 -1.636852e-02
sample124 -0.0460701050 1.814758e-02
sample125 0.0543846585 2.075898e-03
sample126 -0.0729417144 3.276659e-02
sample127 -0.0609509157 -3.270814e-03
sample128 0.0908136899 3.758801e-02
sample129 0.0552445878 -1.879062e-02
sample130 0.0007128089 -1.294308e-02
sample131 -0.0693311345 7.357082e-03
sample132 -0.0556565156 3.126995e-02
sample133 0.0375870104 -1.977240e-02
sample134 -0.1229130924 3.159495e-02
sample135 0.0555550315 -5.563250e-04
sample136 -0.0159768414 -2.046339e-02
sample137 -0.0412337694 -1.151652e-02
sample138 -0.0180604476 -2.526505e-02
sample139 -0.0465649201 1.040683e-02
sample140 0.0452288969 -1.876279e-02
sample141 -0.0189142561 2.247042e-02
sample142 0.0297545566 1.280524e-02
sample143 0.0064292003 -1.997706e-02
sample144 -0.0124284903 -6.369733e-03
sample145 -0.0377141491 5.066743e-02
sample146 -0.0296240067 -3.344465e-02
sample147 0.0726083535 -1.239968e-02
sample148 -0.0284795794 3.389732e-02
sample149 0.0082261455 -6.399305e-02
sample150 -0.0765013197 2.704021e-02
sample151 -0.0220567356 -1.178159e-02
sample152 0.0403422737 -2.714879e-02
sample153 0.0629117719 7.425085e-02
sample154 0.0551622927 -3.548984e-02
sample155 0.0654439133 -1.005306e-02
sample156 0.0209310714 -1.390213e-02
sample157 0.0851522597 6.577150e-03
sample158 0.0208354599 -4.663078e-03
sample159 -0.0498794349 1.913257e-02
sample160 0.0216074437 1.656579e-02
sample161 -0.0075742328 -2.455676e-02
sample162 0.0963663017 5.705881e-02
sample163 -0.1009542191 7.174224e-02
sample164 0.0109881996 1.026806e-03
sample165 -0.0053146157 -6.772855e-03
sample166 -0.0275757357 2.673084e-02
sample167 -0.0825048036 2.278863e-03
sample168 0.0486147429 1.793843e-02
sample169 0.0302506727 8.984253e-03
> o2plsRes@scores$common[[2]] ## Common scores for Block 2
[,1] [,2]
sample1 -0.0621842115 -1.364509e-02
sample2 0.0944623785 9.720892e-03
sample3 0.0406196267 -2.236338e-02
sample4 -0.0229316496 -3.932487e-04
sample5 -0.0157330047 3.231033e-03
sample6 -0.0945794025 3.120720e-02
sample7 -0.0854427118 -1.052880e-02
sample8 -0.1376625920 4.286608e-02
sample9 -0.0377115311 -1.415134e-02
sample10 0.0035244506 1.280825e-02
sample11 0.0016639987 -1.717895e-02
sample12 -0.0781403168 1.884368e-02
sample13 0.0938400516 2.838858e-02
sample14 -0.0759839772 1.810989e-02
sample15 -0.0068340837 -2.705361e-03
sample16 -0.0590150849 4.757848e-02
sample17 0.1178805097 2.040526e-02
sample18 0.0767858320 1.756604e-02
sample19 0.0157112113 -2.172867e-02
sample20 0.0485318300 -2.327033e-02
sample21 0.0185928176 4.777095e-02
sample22 -0.0191358702 -2.329775e-02
sample23 -0.0672994194 -1.535656e-03
sample24 0.1047476642 5.935707e-02
sample25 0.0329844953 -1.358036e-02
sample26 0.1154952052 1.741529e-02
sample27 0.0133849853 -3.590922e-02
sample28 0.0821554039 2.042376e-02
sample29 -0.0567643690 -2.123848e-02
sample30 0.1016073931 -1.134728e-03
sample31 -0.0880396372 3.670548e-02
sample32 0.0300363338 1.182406e-02
sample33 -0.0467252272 3.739254e-03
sample34 0.0783666394 1.203777e-02
sample35 0.0424227097 -1.118559e-02
sample36 -0.1107646166 -1.143464e-02
sample37 -0.0191667664 -2.246060e-02
sample38 0.0155968095 -2.909621e-02
sample39 0.0746847148 7.148218e-03
sample40 -0.0517028178 -2.137267e-02
sample41 0.0234979494 -3.723018e-02
sample42 0.0388797356 -8.557228e-03
sample43 0.0149555568 7.210002e-03
sample44 -0.1150305613 3.461805e-02
sample45 0.0846146236 3.486020e-02
sample46 0.0884426404 -3.246853e-02
sample47 0.0748644971 -8.083045e-03
sample48 -0.0012033198 -9.403647e-03
sample49 -0.0872662737 3.616245e-02
sample50 0.0066941314 -5.284863e-02
sample51 -0.0411777630 3.791830e-02
sample52 -0.0379355780 2.180834e-02
sample53 -0.0851639886 4.751761e-02
sample54 0.0288006248 7.184424e-03
sample55 -0.0164920835 5.919925e-05
sample56 0.0355115616 1.951043e-02
sample57 -0.0141146068 3.492409e-02
sample58 -0.0015636132 9.862883e-03
sample59 -0.0390656483 3.590929e-03
sample60 -0.0139454780 3.963030e-03
sample61 -0.0106410274 1.919705e-02
sample62 0.0236748439 -5.922677e-03
sample63 -0.0846790877 3.839102e-02
sample64 -0.1202581015 2.846469e-02
sample65 0.0050548584 6.328644e-03
sample66 0.0028013072 1.291807e-02
sample67 -0.1231623009 -2.112565e-02
sample68 -0.0437782161 -2.845072e-02
sample69 -0.0501199692 2.053469e-03
sample70 -0.0140278645 -2.027157e-02
sample71 0.0057489505 -4.085977e-02
sample72 0.0511212704 -5.522408e-03
sample73 0.0828141409 7.431582e-03
sample74 -0.0085959456 1.772951e-02
sample75 -0.0312180394 -6.636869e-03
sample76 -0.0519051781 -1.640191e-02
sample77 -0.0925924762 -6.907800e-03
sample78 0.1163971046 2.251122e-02
sample79 -0.0240906926 -4.887766e-02
sample80 -0.0221327065 -6.730703e-03
sample81 -0.0072114968 -2.254399e-02
sample82 0.1204416674 -9.907422e-03
sample83 0.0386739485 -1.171663e-03
sample84 0.0195988488 -1.033806e-02
sample85 -0.0877680171 -1.725057e-03
sample86 0.1023541048 -1.062501e-02
sample87 0.0425213089 -1.356865e-02
sample88 0.0244788514 1.180820e-02
sample89 0.0804276691 2.188588e-02
sample90 -0.0074639871 -6.140721e-03
sample91 -0.1278832404 -6.485140e-02
sample92 -0.0162199697 -5.048358e-02
sample93 0.0769344893 -3.045135e-03
sample94 -0.0104345587 -3.593172e-03
sample95 -0.0260058453 -2.330475e-02
sample96 -0.0025018700 -1.433516e-02
sample97 -0.0492358305 7.774183e-03
sample98 0.0279220220 -3.862141e-03
sample99 0.0813921923 3.487339e-02
sample100 -0.0428797405 7.112807e-03
sample101 0.0032855240 -4.940743e-02
sample102 0.0038439317 2.938008e-03
sample103 0.0358511139 -2.831881e-02
sample104 -0.0162784000 -1.815061e-02
sample105 0.0314853405 -4.656633e-03
sample106 0.0726456731 1.192390e-02
sample107 0.0807342975 7.508627e-03
sample108 0.0688338003 -3.336161e-03
sample109 -0.0694151950 -2.800146e-02
sample110 0.0961218924 -2.111997e-03
sample111 -0.0217900036 -2.864702e-02
sample112 0.0599954082 8.820317e-03
sample113 -0.0195006577 1.128215e-02
sample114 -0.0032126533 -2.682851e-02
sample115 -0.0251101087 -2.221077e-02
sample116 -0.0625141551 -2.137258e-02
sample117 -0.0440473375 -2.806256e-02
sample118 -0.0532042630 -7.590494e-03
sample119 -0.0848603028 -7.133574e-02
sample120 -0.0588832131 6.937326e-03
sample121 0.0613899126 2.915307e-02
sample122 0.0218424338 2.241775e-02
sample123 0.0809008460 -1.051759e-02
sample124 -0.0472109313 1.239887e-02
sample125 0.0583180947 2.521167e-03
sample126 -0.0753941872 2.256455e-02
sample127 -0.0649774209 -3.496964e-03
sample128 0.1000212216 2.908091e-02
sample129 0.0568033049 -1.269016e-02
sample130 -0.0002370832 -9.419675e-03
sample131 -0.0727030877 4.091672e-03
sample132 -0.0566219024 2.179861e-02
sample133 0.0384172955 -1.372840e-02
sample134 -0.1280862736 2.077912e-02
sample135 0.0592633273 6.106685e-04
sample136 -0.0187635410 -1.521173e-02
sample137 -0.0449958970 -9.152840e-03
sample138 -0.0211348699 -1.875415e-02
sample139 -0.0482882861 6.729304e-03
sample140 0.0468926306 -1.285498e-02
sample141 -0.0186248693 1.605439e-02
sample142 0.0328031246 9.887746e-03
sample143 0.0052919839 -1.445666e-02
sample144 -0.0140067923 -4.867248e-03
sample145 -0.0361804310 3.625323e-02
sample146 -0.0345286735 -2.493652e-02
sample147 0.0765025670 -7.714769e-03
sample148 -0.0276016641 2.420589e-02
sample149 0.0027545308 -4.653007e-02
sample150 -0.0792296010 1.831289e-02
sample151 -0.0245894512 -8.991738e-03
sample152 0.0409796547 -1.907063e-02
sample153 0.0734301757 5.528780e-02
sample154 0.0557740684 -2.487723e-02
sample155 0.0689436560 -6.127635e-03
sample156 0.0212272938 -9.747423e-03
sample157 0.0911931194 6.355708e-03
sample158 0.0220840645 -3.016357e-03
sample159 -0.0513244242 1.304175e-02
sample160 0.0246213576 1.248444e-02
sample161 -0.0100369130 -1.805391e-02
sample162 0.1078802043 4.337260e-02
sample163 -0.1017965082 5.047171e-02
sample164 0.0119430799 9.593002e-04
sample165 -0.0063708014 -5.032148e-03
sample166 -0.0283181180 1.899222e-02
sample167 -0.0872832229 1.516582e-04
sample168 0.0540714512 1.397701e-02
sample169 0.0328432652 7.104347e-03
> o2plsRes@scores$dist[[1]] ## Distinctive scores for Block 1
[,1] [,2]
sample1 0.0133684846 2.195848e-02
sample2 0.0254157197 -1.058416e-02
sample3 -0.0049551479 -4.840017e-03
sample4 0.0310390570 -1.063929e-02
sample5 0.0046941318 -6.488426e-03
sample6 -0.0107406753 -1.026702e-02
sample7 -0.0225157631 2.624712e-04
sample8 0.0141320952 -9.505821e-03
sample9 0.0029681280 2.078210e-02
sample10 0.0131729174 -2.275042e-03
sample11 -0.0004164298 1.994019e-02
sample12 -0.0095211620 3.759883e-02
sample13 0.0091018604 -7.953956e-03
sample14 -0.0106557524 -9.181659e-03
sample15 -0.0249924121 3.262724e-02
sample16 -0.0156216400 1.375700e-02
sample17 -0.0019382446 1.073994e-03
sample18 -0.0221072481 -8.703592e-03
sample19 0.0146917619 -1.311712e-02
sample20 -0.0160353760 1.826290e-02
sample21 0.0035947899 -9.616341e-03
sample22 -0.0225060762 -2.532589e-03
sample23 0.0310000683 3.033060e-03
sample24 0.0499544372 1.809450e-02
sample25 0.0284442301 -1.932558e-02
sample26 0.0188220043 2.146985e-02
sample27 -0.0257763219 -1.999228e-03
sample28 0.0120888648 1.125834e-02
sample29 -0.0236482520 4.426726e-02
sample30 -0.0385486305 -2.055935e-02
sample31 -0.0181539336 -5.877838e-03
sample32 -0.0302630460 -2.607192e-03
sample33 -0.0319565715 -1.562628e-02
sample34 -0.0197970124 9.906813e-03
sample35 -0.0247412713 -5.434440e-03
sample36 -0.0386259060 -3.190394e-02
sample37 -0.0566199273 -4.192574e-02
sample38 -0.0142060273 2.259644e-02
sample39 0.0053589035 1.076485e-02
sample40 -0.0552546493 -3.819896e-02
sample41 -0.0013089975 9.278818e-05
sample42 0.0137252142 -1.664652e-02
sample43 -0.0151259626 -6.290953e-03
sample44 0.0617391754 -1.442883e-02
sample45 0.0231410886 1.163143e-03
sample46 -0.0148898209 -1.384176e-04
sample47 -0.0187252536 1.221690e-02
sample48 0.0432839432 1.416671e-02
sample49 0.0160818605 -3.588745e-02
sample50 0.0059333545 4.067003e-02
sample51 -0.0142914866 7.776270e-03
sample52 -0.0086339952 7.208917e-03
sample53 -0.0207386980 6.272432e-03
sample54 -0.0039856719 -1.316934e-02
sample55 -0.0056217017 5.692315e-03
sample56 0.0000123292 8.978290e-04
sample57 -0.0095805555 1.324253e-02
sample58 -0.0124160295 -7.326376e-03
sample59 -0.0400195442 -1.349736e-02
sample60 -0.0460063358 2.770091e-02
sample61 -0.0245266456 1.470710e-02
sample62 -0.0366022783 -3.437352e-03
sample63 0.0013742171 3.288796e-02
sample64 -0.0070599859 2.739588e-02
sample65 0.0041201911 1.498268e-02
sample66 0.0143173351 -1.968812e-02
sample67 -0.0467477531 -1.929938e-02
sample68 -0.0306751978 -1.436184e-02
sample69 -0.0125317217 4.130407e-03
sample70 -0.0068071487 8.080857e-03
sample71 0.0169170264 -7.027348e-03
sample72 -0.0346909749 -1.333770e-02
sample73 -0.0280506153 1.493843e-02
sample74 -0.0182611498 3.294697e-03
sample75 -0.0120563964 8.974612e-03
sample76 0.0001437236 -4.253184e-02
sample77 0.0065330299 -5.252886e-02
sample78 0.0288278141 -1.127782e-02
sample79 0.0503961481 -1.023318e-02
sample80 -0.0207693429 3.648391e-02
sample81 0.0163562768 -9.074596e-03
sample82 -0.0084317129 -1.478976e-02
sample83 -0.0474097918 -1.103126e-02
sample84 0.0177181395 -7.191197e-03
sample85 -0.0342718548 -3.082360e-02
sample86 -0.0261671791 -1.089491e-02
sample87 -0.0009486358 -2.411514e-02
sample88 0.0020528931 -2.894615e-02
sample89 -0.0189361111 -2.638639e-03
sample90 -0.0009863658 -2.390075e-02
sample91 -0.0124352695 8.153234e-02
sample92 0.0564264106 -8.909537e-03
sample93 -0.0081461774 1.570851e-02
sample94 -0.0054896581 1.547251e-02
sample95 0.0224073150 -4.374348e-04
sample96 0.0173528924 -3.050441e-03
sample97 0.0067948115 5.008237e-03
sample98 -0.0116030825 1.498764e-02
sample99 0.0246422688 -4.054795e-03
sample100 -0.0069420745 -4.846343e-04
sample101 0.0124923691 3.091503e-02
sample102 0.0650835386 -1.367400e-02
sample103 -0.0042741828 7.855985e-03
sample104 0.0250591040 -4.171938e-03
sample105 0.0157516368 -3.121990e-02
sample106 0.0060593853 -5.101693e-03
sample107 -0.0098329626 1.044506e-02
sample108 0.0044269853 4.142036e-03
sample109 0.0572473486 1.517542e-02
sample110 0.0090474827 -5.119868e-03
sample111 0.0444263015 7.983232e-03
sample112 -0.0131765484 -9.696342e-04
sample113 0.0241047399 6.706740e-03
sample114 0.0074558775 -4.728652e-03
sample115 0.0611851433 1.117210e-02
sample116 0.0432646951 -1.380556e-02
sample117 0.0516750066 -3.575617e-02
sample118 0.0139942100 -3.279138e-03
sample119 0.0291722987 5.587946e-02
sample120 0.0103515853 -1.690016e-03
sample121 -0.0091396331 3.552116e-02
sample122 0.0260431679 -7.583975e-03
sample123 -0.0076666389 -1.628489e-02
sample124 0.0283466326 3.127845e-03
sample125 0.0016472378 -2.770692e-02
sample126 -0.0286529417 3.489336e-02
sample127 -0.0010224500 7.483214e-03
sample128 0.0209049296 2.572016e-02
sample129 -0.0218184878 -1.755347e-02
sample130 -0.0005009620 -1.697978e-02
sample131 -0.0134032968 4.637390e-03
sample132 0.0198526786 5.723983e-04
sample133 0.0088812957 -9.988115e-03
sample134 -0.0137484514 1.172591e-02
sample135 -0.0220314568 1.347465e-02
sample136 -0.0185173353 5.168079e-03
sample137 -0.0248352123 -9.472788e-03
sample138 0.0301635767 -1.175283e-02
sample139 -0.0173576929 -3.872592e-02
sample140 -0.0262157762 2.456863e-02
sample141 0.0058369763 -1.420854e-02
sample142 0.0207886071 -1.188764e-02
sample143 0.0092832598 -1.324238e-02
sample144 0.0028442140 3.627979e-03
sample145 0.0199749569 2.862202e-03
sample146 -0.0182236697 1.726556e-03
sample147 -0.0282519995 -2.825595e-02
sample148 0.0065435868 -1.572917e-02
sample149 0.0158233820 -2.159451e-02
sample150 -0.0177383738 -3.020633e-03
sample151 0.0245166984 -6.888241e-03
sample152 0.0107259913 3.314630e-02
sample153 0.0550963965 3.758760e-02
sample154 -0.0131452472 -8.153903e-04
sample155 -0.0211742574 2.642246e-03
sample156 -0.0117803505 2.698265e-02
sample157 -0.0096167165 1.433840e-02
sample158 -0.0101754772 9.137620e-03
sample159 0.0120662931 -2.565236e-02
sample160 -0.0132238202 2.916023e-03
sample161 0.0274491966 -1.748284e-02
sample162 0.0012482909 3.152261e-02
sample163 0.0042031315 1.830701e-02
sample164 0.0174896157 -1.175915e-02
sample165 0.0097517662 -6.119019e-03
sample166 0.0190134679 -1.121582e-02
sample167 -0.0044140836 4.665585e-03
sample168 0.0049689168 -1.941822e-02
sample169 -0.0209802098 3.498729e-03
> o2plsRes@scores$dist[[2]] ## Distinctive scores for Block 2
[,1] [,2]
sample1 -0.0515543627 -0.0305856787
sample2 -0.0144993256 0.0236342950
sample3 -0.0371833108 -0.0140263348
sample4 0.0068945388 -0.0132539692
sample5 0.0215035333 -0.0663338101
sample6 -0.0187055152 0.0088773016
sample7 -0.0061521552 0.0064029054
sample8 -0.0210874459 0.0334652901
sample9 0.0516865043 -0.0291142799
sample10 0.0059440366 -0.0527217447
sample11 0.0393010793 -0.0200624712
sample12 -0.0420837100 0.0131331362
sample13 0.0333252565 0.0818552509
sample14 -0.0190062644 0.0160202175
sample15 -0.0030968049 -0.0189230681
sample16 -0.0004452158 0.0018880102
sample17 -0.0185848615 0.0240170131
sample18 -0.0273093598 0.0230213640
sample19 -0.0217761111 -0.0445894441
sample20 0.0245820821 0.0159812738
sample21 0.0034527644 -0.0400016054
sample22 -0.0340789054 0.0039289109
sample23 -0.0010344929 -0.0310161212
sample24 0.0289468503 0.0760962436
sample25 -0.0119098496 -0.0122798760
sample26 -0.0181001057 0.0517892852
sample27 0.0050465417 -0.0086515844
sample28 0.0057491502 0.0358830107
sample29 -0.0051104246 0.0116605117
sample30 -0.0103085904 0.0039678538
sample31 -0.0319929858 0.0090606113
sample32 -0.0036232521 -0.0328202010
sample33 -0.0534742153 0.0024751837
sample34 -0.0067495749 -0.0111000311
sample35 0.0378745721 0.0465929296
sample36 0.0647886800 0.0359987924
sample37 0.0488441236 0.0492906912
sample38 -0.0251514062 0.0197110110
sample39 -0.0085428066 -0.0105117852
sample40 0.0379324087 0.0440810741
sample41 -0.0044199152 -0.0128820644
sample42 -0.0292553573 -0.0067045265
sample43 -0.0077829155 -0.0510178219
sample44 0.0045122248 0.0479660309
sample45 -0.0074444298 -0.0051116726
sample46 -0.0088025512 0.0196186661
sample47 0.0076696301 0.0215947965
sample48 0.0290108585 -0.0175568376
sample49 -0.0141754858 0.0184717099
sample50 0.0006282201 -0.0233054373
sample51 0.0441995177 -0.0410022921
sample52 0.0715329391 -0.0399499475
sample53 -0.0095954087 -0.0029140909
sample54 0.0048933768 -0.0281884386
sample55 0.0327325487 -0.0532290012
sample56 0.0323068984 -0.0256595538
sample57 0.0806603122 -0.0286748097
sample58 -0.0064792049 -0.0006945349
sample59 0.0088958941 0.0067389649
sample60 0.0874124612 0.0431964341
sample61 0.0577604571 -0.0326112099
sample62 -0.0313318464 0.0224391756
sample63 -0.0233625220 0.0125110562
sample64 -0.0086426068 0.0148770341
sample65 0.0025256193 -0.0404466327
sample66 0.0006014071 -0.0471576264
sample67 0.0706087042 0.0516228406
sample68 0.0082301011 0.0033109509
sample69 -0.0475076743 0.0001452708
sample70 -0.0600773716 0.0089986962
sample71 -0.0096321627 -0.0050761187
sample72 -0.0031773546 -0.0166221542
sample73 -0.0113700517 -0.0191726684
sample74 -0.0014179662 -0.0608101325
sample75 0.0041911740 -0.0399981269
sample76 -0.0055326449 0.0353114263
sample77 -0.0260214459 0.0305731380
sample78 -0.0119267436 0.0632236007
sample79 0.0186017239 0.0027402910
sample80 0.0241047889 -0.0472697181
sample81 -0.0220288317 -0.0079577210
sample82 -0.0180751258 0.0639051029
sample83 -0.0256671713 -0.0125898269
sample84 0.0161392598 -0.0567222449
sample85 0.0139988188 0.0322763454
sample86 -0.0198382995 0.0389225776
sample87 0.0266270281 -0.0032979996
sample88 0.0515677078 0.0117902495
sample89 0.0014022125 -0.0140510488
sample90 -0.0375949749 0.0044004551
sample91 0.0310397965 0.0440610926
sample92 0.0270570567 0.0324380452
sample93 -0.0215009202 0.0063993941
sample94 -0.0415702912 -0.0037692077
sample95 -0.0168416047 0.0010019120
sample96 -0.0285582661 -0.0187991000
sample97 -0.0490843868 -0.0266760748
sample98 -0.0171579033 -0.0112897471
sample99 -0.0271316525 0.0232395583
sample100 -0.0301789816 0.0305498693
sample101 -0.0264371151 0.0170723968
sample102 0.0012767734 -0.0248949597
sample103 0.0055214687 -0.0030040587
sample104 0.0251346074 -0.0165212671
sample105 0.0062424215 -0.0400309901
sample106 0.0069768684 0.0154982315
sample107 -0.0315912602 -0.0118883820
sample108 -0.0109690679 0.0023637162
sample109 -0.0014762845 0.0165583675
sample110 0.0036971063 0.0168260726
sample111 -0.0071624739 -0.0345651461
sample112 0.0046098120 -0.0048009350
sample113 0.0082236008 -0.0383233357
sample114 -0.0293642209 -0.0165595240
sample115 -0.0003260453 0.0135805368
sample116 0.0183575759 0.0665377581
sample117 0.0227640036 -0.0012287760
sample118 0.0015695248 0.0472617382
sample119 0.0190084932 0.0590034062
sample120 -0.0449645755 0.0072755697
sample121 0.0077307184 0.0104738937
sample122 -0.0027132063 -0.0394983138
sample123 0.0016959300 0.0028593594
sample124 -0.0365091615 0.0040382925
sample125 -0.0053658663 -0.0316029164
sample126 -0.0458032408 0.0019165544
sample127 -0.0494064872 0.0088209044
sample128 -0.0155454766 0.0186819802
sample129 -0.0184340400 0.0038684312
sample130 -0.0303640987 -0.0052225766
sample131 -0.0088697422 0.0156339713
sample132 -0.0433916471 -0.0154075483
sample133 0.0204029276 -0.0282209049
sample134 0.0175513332 0.0262883962
sample135 0.0029009925 0.0017003151
sample136 -0.0367997573 -0.0072249751
sample137 -0.0348600323 0.0075400273
sample138 -0.0044063824 -0.0053752428
sample139 0.0073103935 0.0308956174
sample140 0.0039925654 -0.0167019605
sample141 -0.0184093462 -0.0387953445
sample142 0.0268670676 -0.0239229634
sample143 0.0421049126 -0.0110888235
sample144 0.0017253664 -0.0341766012
sample145 0.0681741320 -0.0073526377
sample146 -0.0239965222 0.0118396767
sample147 -0.0063453522 0.0183130585
sample148 0.0230825251 -0.0379753037
sample149 0.0223298673 0.0188909118
sample150 0.0055709108 0.0174179009
sample151 0.0039177786 -0.0233533275
sample152 0.0134325667 0.0302344591
sample153 0.0511990309 0.0730230140
sample154 0.0006698324 0.0154177486
sample155 0.0032926626 -0.0288651601
sample156 -0.0016463495 -0.0474657733
sample157 -0.0045857599 0.0154934573
sample158 0.0201775524 -0.0332982124
sample159 -0.0086909001 0.0073496711
sample160 0.0295437331 -0.0555734536
sample161 0.0332754288 0.0033779619
sample162 0.0121954537 0.0433540412
sample163 -0.0173490933 0.0227219128
sample164 0.0143374783 -0.0453542590
sample165 0.0343612593 -0.0511194536
sample166 -0.0157536004 0.0094621170
sample167 -0.0179654624 -0.0006982358
sample168 -0.0033829919 0.0060747155
sample169 0.0116231468 -0.0015112800
>
> ## 3.3 Plotting VAF
>
> # DISCO-SCA plotVAF
> plotVAF(discoRes)
>
> # JIVE plotVAF
> plotVAF(jiveRes)
>
>
> #########################
> ## PART 4. Plot Results
>
> # Scores for common part. DISCO-SCA
> plotRes(object=discoRes,comps=c(1,2),what="scores",type="common",
+ combined=FALSE,block=NULL,color="classname",shape=NULL,labels=NULL,
+ background=TRUE,palette=NULL,pointSize=4,labelSize=NULL,
+ axisSize=NULL,titleSize=NULL)
Warning message:
`aes_string()` was deprecated in ggplot2 3.0.0.
ℹ Please use tidy evaluation idioms with `aes()`.
ℹ See also `vignette("ggplot2-in-packages")` for more information.
ℹ The deprecated feature was likely used in the STATegRa package.
Please report the issue to the authors.
>
> # Scores for common part. JIVE
> plotRes(object=jiveRes,comps=c(1,2),what="scores",type="common",
+ combined=FALSE,block=NULL,color="classname",shape=NULL,labels=NULL,
+ background=TRUE,palette=NULL,pointSize=4,labelSize=NULL,
+ axisSize=NULL,titleSize=NULL)
>
> # Scores for common part. O2PLS.
> p1 <- plotRes(object=o2plsRes,comps=c(1,2),what="scores",type="common",
+ combined=FALSE,block="expr",color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
> p2 <- plotRes(object=o2plsRes,comps=c(1,2),what="scores",type="common",
+ combined=FALSE,block="mirna",color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
> legend <- g_legend(p1)
> grid.arrange(arrangeGrob(p1+theme(legend.position="none"),
+ p2+theme(legend.position="none"),nrow=1),
+ legend,heights=c(6/7,1/7))
>
> # Combined plot of scores for common part. O2PLS.
> plotRes(object=o2plsRes,comps=c(1,1),what="scores",type="common",
+ combined=TRUE,block=NULL,color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
>
>
> # Scores for distinctive part. DISCO-SCA. (two plots one for each block)
> p1 <- plotRes(object=discoRes,comps=c(1,2),what="scores",type="individual",
+ combined=FALSE,block="expr",color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
> p2 <- plotRes(object=discoRes,comps=c(1,2),what="scores",type="individual",
+ combined=FALSE,block="mirna",color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
> legend <- g_legend(p1)
> grid.arrange(arrangeGrob(p1+theme(legend.position="none"),
+ p2+theme(legend.position="none"),nrow=1),
+ legend,heights=c(6/7,1/7))
>
> # Combined plot of scores for distinctive part. DISCO-SCA
> plotRes(object=discoRes,comps=c(1,1),what="scores",type="individual",
+ combined=TRUE,block=NULL,color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
>
> # Combined plot of scores for common and distinctive part. O2PLS (two plots one for each block)
> p1 <- plotRes(object=o2plsRes,comps=c(1,1),what="scores",type="both",
+ combined=FALSE,block="expr",color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
> p2 <- plotRes(object=o2plsRes,comps=c(1,1),what="scores",type="both",
+ combined=FALSE,block="mirna",color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
> legend <- g_legend(p1)
> grid.arrange(arrangeGrob(p1+theme(legend.position="none"),
+ p2+theme(legend.position="none"),nrow=1),
+ legend,heights=c(6/7,1/7))
>
> # Combined plot of scores for common and distinctive part. DISCO (two plots one for each block)
> p1 <- plotRes(object=discoRes,comps=c(1,1),what="scores",type="both",
+ combined=FALSE,block="expr",color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
> p2 <- plotRes(object=discoRes,comps=c(1,1),what="scores",type="both",
+ combined=FALSE,block="mirna",color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
> legend <- g_legend(p1)
> grid.arrange(arrangeGrob(p1+theme(legend.position="none"),
+ p2+theme(legend.position="none"),nrow=1),
+ legend,heights=c(6/7,1/7))
>
> # Loadings for common part. DISCO-SCA. (two plots one for each block)
> p1 <- plotRes(object=discoRes,comps=c(1,2),what="loadings",type="common",
+ combined=FALSE,block="expr",color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
> p2 <- plotRes(object=discoRes,comps=c(1,2),what="loadings",type="common",
+ combined=FALSE,block="mirna",color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
> grid.arrange(arrangeGrob(p1+theme(legend.position="none"),
+ p2+theme(legend.position="none"),nrow=1),
+ heights=c(6/7,1/7))
>
>
> # Loadings for distinctive part. DISCO-SCA. (two plots one for each block)
> p1 <- plotRes(object=discoRes,comps=c(1,2),what="loadings",type="individual",
+ combined=FALSE,block="expr",color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
> p2 <- plotRes(object=discoRes,comps=c(1,2),what="loadings",type="individual",
+ combined=FALSE,block="mirna",color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
> grid.arrange(arrangeGrob(p1+theme(legend.position="none"),
+ p2+theme(legend.position="none"),nrow=1),
+ heights=c(6/7,1/7))
>
>
> # Combined plot for loadings from common and distinctive part (two plots one for each block)
> p1 <- plotRes(object=discoRes,comps=c(1,1),what="loadings",type="both",
+ combined=FALSE,block="expr",color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
> p2 <- plotRes(object=discoRes,comps=c(1,1),what="loadings",type="both",
+ combined=FALSE,block="mirna",color="classname",shape=NULL,
+ labels=NULL,background=TRUE,palette=NULL,pointSize=4,
+ labelSize=NULL,axisSize=NULL,titleSize=NULL)
> grid.arrange(arrangeGrob(p1+theme(legend.position="none"),
+ p2+theme(legend.position="none"),nrow=1),
+ heights=c(6/7,1/7))
>
>
>
> ## Plot scores and loadings togheter: Common components DISCO-SCA
> p1 <- plotRes(object=discoRes,comps=c(1,2),what="both",type="common",
+ combined=FALSE,block="expr",color="classname",shape=NULL,labels=NULL,
+ background=TRUE,palette=NULL,pointSize=4,labelSize=NULL,
+ axisSize=NULL,titleSize=NULL)
> p2 <- plotRes(object=discoRes,comps=c(1,2),what="both",type="common",
+ combined=FALSE,block="mirna",color="classname",shape=NULL,labels=NULL,
+ background=TRUE,palette=NULL,pointSize=4,labelSize=NULL,
+ axisSize=NULL,titleSize=NULL)
> grid.arrange(arrangeGrob(p1+theme(legend.position="none"),
+ p2+theme(legend.position="none"),nrow=1),
+ heights=c(6/7,1/7))
>
>
> ## Plot scores and loadings togheter: Common components O2PLS
> p1 <- plotRes(object=o2plsRes,comps=c(1,2),what="both",type="common",
+ combined=FALSE,block="expr",color="classname",shape=NULL,labels=NULL,
+ background=TRUE,palette=NULL,pointSize=4,labelSize=NULL,
+ axisSize=NULL,titleSize=NULL)
> p2 <- plotRes(object=o2plsRes,comps=c(1,2),what="both",type="common",
+ combined=FALSE,block="mirna",color="classname",shape=NULL,labels=NULL,
+ background=TRUE,palette=NULL,pointSize=4,labelSize=NULL,
+ axisSize=NULL,titleSize=NULL)
> grid.arrange(arrangeGrob(p1+theme(legend.position="none"),
+ p2+theme(legend.position="none"),nrow=1),
+ heights=c(6/7,1/7))
>
>
> ## Plot scores and loadings togheter: Distintive components DISCO-SCA
> p1 <- plotRes(object=discoRes,comps=c(1,2),what="both",type="individual",
+ combined=FALSE,block="expr",color="classname",shape=NULL,labels=NULL,
+ background=TRUE,palette=NULL,pointSize=4,labelSize=NULL,
+ axisSize=NULL,titleSize=NULL)
> p2 <- plotRes(object=discoRes,comps=c(1,2),what="both",type="individual",
+ combined=FALSE,block="mirna",color="classname",shape=NULL,labels=NULL,
+ background=TRUE,palette=NULL,pointSize=4,labelSize=NULL,
+ axisSize=NULL,titleSize=NULL)
> grid.arrange(arrangeGrob(p1+theme(legend.position="none"),
+ p2+theme(legend.position="none"),nrow=1),
+ heights=c(6/7,1/7))
>
>
>
>
> proc.time()
user system elapsed
14.448 0.321 14.760
STATegRa.Rcheck/STATegRa-Ex.timings
| name | user | system | elapsed | |
| STATegRaUsersGuide | 0.001 | 0.000 | 0.001 | |
| STATegRa_data | 0.242 | 0.009 | 0.251 | |
| STATegRa_data_TCGA_BRCA | 0.004 | 0.000 | 0.003 | |
| bioDist | 0.424 | 0.047 | 0.473 | |
| bioDistFeature | 0.308 | 0.019 | 0.328 | |
| bioDistFeaturePlot | 0.308 | 0.032 | 0.339 | |
| bioDistW | 0.317 | 0.013 | 0.329 | |
| bioDistWPlot | 0.308 | 0.006 | 0.313 | |
| bioMap | 0.002 | 0.001 | 0.003 | |
| combiningMappings | 0.010 | 0.001 | 0.010 | |
| createOmicsExpressionSet | 0.139 | 0.002 | 0.141 | |
| getInitialData | 0.576 | 0.026 | 0.601 | |
| getLoadings | 0.584 | 0.043 | 0.627 | |
| getMethodInfo | 0.660 | 0.009 | 0.670 | |
| getPreprocessing | 0.698 | 0.701 | 1.399 | |
| getScores | 0.705 | 0.053 | 0.758 | |
| getVAF | 0.587 | 0.007 | 0.593 | |
| holistOmics | 0.001 | 0.002 | 0.002 | |
| modelSelection | 1.689 | 1.740 | 3.428 | |
| omicsCompAnalysis | 3.918 | 0.047 | 3.965 | |
| omicsNPC | 0.002 | 0.001 | 0.002 | |
| plotRes | 5.267 | 0.070 | 5.337 | |
| plotVAF | 4.598 | 0.017 | 4.617 | |