R Under development (unstable) (2025-08-18 r88641 ucrt) -- "Unsuffered Consequences" Copyright (C) 2025 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 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. > library("ACNE") Loading required package: aroma.affymetrix Loading required package: R.utils Loading required package: R.oo Loading required package: R.methodsS3 R.methodsS3 v1.8.2 (2022-06-13 22:00:14 UTC) successfully loaded. See ?R.methodsS3 for help. R.oo v1.27.1 (2025-05-02 21:00:05 UTC) successfully loaded. See ?R.oo for help. Attaching package: 'R.oo' The following object is masked from 'package:R.methodsS3': throw The following objects are masked from 'package:methods': getClasses, getMethods The following objects are masked from 'package:base': attach, detach, load, save R.utils v2.13.0 (2025-02-24 21:20:02 UTC) successfully loaded. See ?R.utils for help. Attaching package: 'R.utils' The following object is masked from 'package:utils': timestamp The following objects are masked from 'package:base': cat, commandArgs, getOption, isOpen, nullfile, parse, use, warnings Loading required package: aroma.core Loading required package: R.filesets R.filesets v2.15.1 (2024-01-24 17:22:49 UTC) successfully loaded. See ?R.filesets for help. Attaching package: 'R.filesets' The following object is masked from 'package:R.utils': validate The following objects are masked from 'package:base': append, readLines Loading required package: R.devices R.devices v2.17.2 (2024-01-29 13:30:11 UTC) successfully loaded. See ?R.devices for help. aroma.core v3.3.2 successfully loaded. See ?aroma.core for help. Attaching package: 'aroma.core' The following objects are masked from 'package:base': .Machine, colMeans, colSums, library, require, write Loading required package: aroma.light aroma.light v3.37.0 (2024-11-03) successfully loaded. See ?aroma.light for help. Attaching package: 'aroma.light' The following objects are masked from 'package:aroma.affymetrix': averageQuantile, normalizeQuantile, plotDensity, plotMvsA, plotXYCurve The following objects are masked from 'package:aroma.core': callNaiveGenotypes, normalizeTumorBoost Loading required package: affxparser aroma.affymetrix v3.2.3 successfully loaded. See ?aroma.affymetrix for help. Attaching package: 'aroma.affymetrix' The following objects are masked _by_ 'package:aroma.light': averageQuantile, normalizeQuantile, plotDensity, plotMvsA, plotXYCurve ACNE v0.9.2 successfully loaded. See ?ACNE for help. Warning message: In .requireBiocPackage("affxparser", neededBy = getName(pkg)) : Package 'affxparser' could not be loaded. Without it aroma.affymetrix will not work. Please install it from Bioconductor, cf. https://www.bioconductor.org/ > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # DATA: Lx2xI allele-specific signals for six different SNPs > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > filenames <- sprintf("V%d.Rbin", 1:6) > pathnames <- system.file("extData", filenames, package="ACNE") > Ys <- lapply(pathnames, FUN=function(p) snpMatrixToArray(loadToEnv(p)$V)) > names(Ys) <- sprintf("SNP #%d", seq_along(Ys)) > > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # ACNE fitting of NMF to the six SNPs > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > for (name in names(Ys)) { + Y <- Ys[[name]] + fit <- fitSnpNmfArray(Y) + str(fit) + plot(fit, lim=c(0,2^14), main=name) + } List of 8 $ W : num [1:20, 1:2] 1350 1631 1981 2648 2067 ... $ H : num [1:2, 1:64] 0.336 1.564 0.141 1.955 0.063 ... $ hasConverged : logi TRUE $ nbrOfIterations: int 6 $ V : num [1:20, 1:64] 1346 1986 1788 1077 1181 ... $ Y : num [1:10, 1:2, 1:64] 1346 1986 1788 1077 1181 ... $ W2 : num [1:10, 1:2, 1:2] 1350 1631 1981 2648 2067 ... $ args : list() - attr(*, "class")= chr [1:2] "list" "SnpNmfFit" num [1:10, 1:2, 1:64] 1346 1986 1788 1077 1181 ... num [1:10, 1:2, 1:64] 1208 1617 1715 1408 1282 ... List of 8 $ W : num [1:20, 1:2] 2219 1891 1819 1713 1423 ... $ H : num [1:2, 1:64] 0.11723 1.14445 0.00001 2.27715 0.04001 ... $ hasConverged : logi TRUE $ nbrOfIterations: int 3 $ V : num [1:20, 1:64] 846 992 1368 732 884 ... $ Y : num [1:10, 1:2, 1:64] 846 992 1368 732 884 ... $ W2 : num [1:10, 1:2, 1:2] 2219 1891 1819 1713 1423 ... $ args : list() - attr(*, "class")= chr [1:2] "list" "SnpNmfFit" num [1:10, 1:2, 1:64] 846 992 1368 732 884 ... num [1:10, 1:2, 1:64] 850 791 747 656 687 ... List of 8 $ W : num [1:20, 1:2] 1985 1909 1841 1953 1681 ... $ H : num [1:2, 1:64] 0.0857 1.7695 0.9967 1.1351 0.1585 ... $ hasConverged : logi TRUE $ nbrOfIterations: int 6 $ V : num [1:20, 1:64] 1109 787 874 766 881 ... $ Y : num [1:10, 1:2, 1:64] 1109 787 874 766 881 ... $ W2 : num [1:10, 1:2, 1:2] 1985 1909 1841 1953 1681 ... $ args : list() - attr(*, "class")= chr [1:2] "list" "SnpNmfFit" num [1:10, 1:2, 1:64] 1109 787 874 766 881 ... num [1:10, 1:2, 1:64] 931 699 683 693 953 ... List of 8 $ W : num [1:20, 1:2] 5805 2376 3127 2874 4924 ... $ H : num [1:2, 1:64] 1.30 9.54e-02 2.34 1.06e-05 1.05 ... $ hasConverged : logi TRUE $ nbrOfIterations: int 5 $ V : num [1:20, 1:64] 6708 3451 4694 3849 5334 ... $ Y : num [1:10, 1:2, 1:64] 6708 3451 4694 3849 5334 ... $ W2 : num [1:10, 1:2, 1:2] 5805 2376 3127 2874 4924 ... $ args : list() - attr(*, "class")= chr [1:2] "list" "SnpNmfFit" num [1:10, 1:2, 1:64] 6708 3451 4694 3849 5334 ... num [1:10, 1:2, 1:64] 7576 3132 4137 3792 6485 ... List of 8 $ W : num [1:20, 1:2] 3859 3395 4423 3084 2972 ... $ H : num [1:2, 1:64] 0.8685 1.2462 0.8915 1.1232 0.0469 ... $ hasConverged : logi TRUE $ nbrOfIterations: int 8 $ V : num [1:20, 1:64] 5181 4257 4253 3400 3720 ... $ Y : num [1:10, 1:2, 1:64] 5181 4257 4253 3400 3720 ... $ W2 : num [1:10, 1:2, 1:2] 3859 3395 4423 3084 2972 ... $ args : list() - attr(*, "class")= chr [1:2] "list" "SnpNmfFit" num [1:10, 1:2, 1:64] 5181 4257 4253 3400 3720 ... num [1:10, 1:2, 1:64] 4666 3783 4914 3561 3462 ... List of 8 $ W : num [1:20, 1:2] 3602 3295 3952 3628 4198 ... $ H : num [1:2, 1:64] 0.1692 2.8918 0.1125 2.0907 0.0683 ... $ hasConverged : logi TRUE $ nbrOfIterations: int 4 $ V : num [1:20, 1:64] 5870 3369 5017 2700 4315 ... $ Y : num [1:10, 1:2, 1:64] 5870 3369 5017 2700 4315 ... $ W2 : num [1:10, 1:2, 1:2] 3602 3295 3952 3628 4198 ... $ args : list() - attr(*, "class")= chr [1:2] "list" "SnpNmfFit" num [1:10, 1:2, 1:64] 5870 3369 5017 2700 4315 ... num [1:10, 1:2, 1:64] 4529 2748 4392 3398 4907 ... > > proc.time() user system elapsed 1.10 0.31 1.40