Back to Multiple platform build/check report for BioC 3.19: simplified long |
|
This page was generated on 2024-04-29 11:37:54 -0400 (Mon, 29 Apr 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" | 4752 |
palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup" | 4486 |
lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.0 beta (2024-04-14 r86421) -- "Puppy Cup" | 4518 |
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" | 4475 |
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 449/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
COTAN 2.3.6 (landing page) Galfrè Silvia Giulia
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | |||||||||
palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | |||||||||
lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | |||||||||
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) / aarch64 | OK | OK | OK | ||||||||||
kjohnson3 | macOS 13.6.5 Ventura / arm64 | see weekly results here | ||||||||||||
To the developers/maintainers of the COTAN package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/COTAN.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: COTAN |
Version: 2.3.6 |
Command: F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:COTAN.install-out.txt --library=F:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings COTAN_2.3.6.tar.gz |
StartedAt: 2024-04-29 00:35:37 -0400 (Mon, 29 Apr 2024) |
EndedAt: 2024-04-29 00:57:21 -0400 (Mon, 29 Apr 2024) |
EllapsedTime: 1304.1 seconds |
RetCode: 0 |
Status: OK |
CheckDir: COTAN.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:COTAN.install-out.txt --library=F:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings COTAN_2.3.6.tar.gz ### ############################################################################## ############################################################################## * using log directory 'F:/biocbuild/bbs-3.19-bioc/meat/COTAN.Rcheck' * using R version 4.4.0 beta (2024-04-15 r86425 ucrt) * using platform: x86_64-w64-mingw32 * R was compiled by gcc.exe (GCC) 13.2.0 GNU Fortran (GCC) 13.2.0 * running under: Windows Server 2022 x64 (build 20348) * using session charset: UTF-8 * using option '--no-vignettes' * checking for file 'COTAN/DESCRIPTION' ... OK * checking extension type ... Package * this is package 'COTAN' version '2.3.6' * 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 whether package 'COTAN' 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 dependencies in R code ... NOTE Unexported object imported by a ':::' call: 'ggplot2:::ggname' See the note in ?`:::` about the use of this operator. * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... NOTE GDIPlot: no visible binding for global variable 'sum.raw.norm' GDIPlot: no visible binding for global variable 'GDI' UMAPPlot: no visible binding for global variable 'x' UMAPPlot: no visible binding for global variable 'y' calculateG: no visible binding for global variable 'observedNN' calculateG: no visible binding for global variable 'observedNY' calculateG: no visible binding for global variable 'observedYN' calculateG: no visible binding for global variable 'observedYY' calculateG: no visible binding for global variable 'expectedNN' calculateG: no visible binding for global variable 'expectedNY' calculateG: no visible binding for global variable 'expectedYN' calculateG: no visible binding for global variable 'expectedYY' calculatePartialCoex: no visible binding for global variable 'expectedNN' calculatePartialCoex: no visible binding for global variable 'expectedNY' calculatePartialCoex: no visible binding for global variable 'expectedYN' calculatePartialCoex: no visible binding for global variable 'expectedYY' calculatePartialCoex: no visible binding for global variable 'observedYY' calculatePartialCoex: no visible binding for global variable '.' cellsUniformClustering: no visible binding for global variable 'objSeurat' cellsUniformClustering: no visible binding for global variable 'usedMaxResolution' checkClusterUniformity: ... may be used in an incorrect context: 'c(..., nuPlot, zoomedNuPlot)' checkClusterUniformity: no visible binding for global variable 'nuPlot' checkClusterUniformity: no visible binding for global variable 'zoomedNuPlot' cleanPlots: no visible binding for global variable 'PC1' cleanPlots: no visible binding for global variable 'PC2' cleanPlots: no visible binding for global variable 'n' cleanPlots: no visible binding for global variable 'means' cleanPlots: no visible binding for global variable 'nu' clustersMarkersHeatmapPlot: no visible binding for global variable 'condName' clustersMarkersHeatmapPlot: no visible binding for global variable 'conditions' clustersSummaryPlot: no visible binding for global variable 'keys' clustersSummaryPlot: no visible binding for global variable 'values' clustersSummaryPlot: no visible binding for global variable 'CellNumber' clustersSummaryPlot: no visible binding for global variable 'ExpGenes' clustersSummaryPlot: no visible binding for global variable 'Cluster' clustersSummaryPlot: no visible binding for global variable 'Condition' establishGenesClusters: no visible binding for global variable 'secondaryMarkers' establishGenesClusters: no visible binding for global variable 'GCS' establishGenesClusters: no visible binding for global variable 'rankGenes' expectedContingencyTables: no visible binding for global variable 'expectedN' expectedPartialContingencyTables: no visible binding for global variable 'expectedNN' expectedPartialContingencyTables: no visible binding for global variable 'expectedN' geom_flat_violin : <anonymous>: no visible binding for global variable 'group' geom_flat_violin : <anonymous>: no visible binding for global variable 'y' geom_flat_violin : <anonymous>: no visible binding for global variable 'x' geom_flat_violin : <anonymous>: no visible binding for global variable 'width' geom_flat_violin : <anonymous>: no visible binding for global variable 'violinwidth' geom_flat_violin : <anonymous>: no visible binding for global variable 'xmax' geom_flat_violin : <anonymous>: no visible binding for global variable 'xminv' geom_flat_violin : <anonymous>: no visible binding for global variable 'xmaxv' heatmapPlot: no visible binding for global variable 'g2' mergeUniformCellsClusters : testPairListMerge: no visible binding for global variable 'cl1' mergeUniformCellsClusters : testPairListMerge: no visible binding for global variable 'cl2' mitochondrialPercentagePlot: no visible binding for global variable 'mit.percentage' observedContingencyTables: no visible binding for global variable 'observedY' observedPartialContingencyTables: no visible binding for global variable 'observedYY' observedPartialContingencyTables: no visible binding for global variable 'observedY' reorderClusterization: no visible global function definition for 'as.dist' scatterPlot: no visible binding for global variable '.x' calculateCoex,COTAN: no visible binding for global variable 'expectedNN' calculateCoex,COTAN: no visible binding for global variable 'expectedNY' calculateCoex,COTAN: no visible binding for global variable 'expectedYN' calculateCoex,COTAN: no visible binding for global variable 'expectedYY' calculateCoex,COTAN: no visible binding for global variable 'observedYY' calculateCoex,COTAN: no visible binding for global variable '.' coerce,COTAN-scCOTAN: no visible binding for global variable 'rawNorm' coerce,COTAN-scCOTAN: no visible binding for global variable 'nu' coerce,COTAN-scCOTAN: no visible binding for global variable 'lambda' coerce,COTAN-scCOTAN: no visible binding for global variable 'a' coerce,COTAN-scCOTAN: no visible binding for global variable 'hk' coerce,COTAN-scCOTAN: no visible binding for global variable 'clusters' coerce,COTAN-scCOTAN: no visible binding for global variable 'clusterData' Undefined global functions or variables: . .x CellNumber Cluster Condition ExpGenes GCS GDI PC1 PC2 a as.dist cl1 cl2 clusterData clusters condName conditions expectedN expectedNN expectedNY expectedYN expectedYY g2 group hk keys lambda means mit.percentage n nu nuPlot objSeurat observedNN observedNY observedY observedYN observedYY rankGenes rawNorm secondaryMarkers sum.raw.norm usedMaxResolution values violinwidth width x xmax xmaxv xminv y zoomedNuPlot Consider adding importFrom("stats", "as.dist") to your NAMESPACE file. * checking Rd files ... OK * checking Rd metadata ... OK * checking Rd cross-references ... OK * 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 UniformClusters 172.99 1.02 173.13 CalculatingCOEX 72.86 1.10 72.96 HeatmapPlots 62.55 1.66 63.41 ParametersEstimations 38.11 0.73 38.80 HandlingClusterizations 25.05 1.54 25.78 GenesCoexSpace 14.69 0.24 14.63 COTANObjectCreation 12.91 0.14 12.80 RawDataCleaning 6.53 0.19 7.06 * checking for unstated dependencies in 'tests' ... OK * checking tests ... Running 'outputTestDatasetCreation.R' Running 'spelling.R' Running 'testthat.R' OK * checking for unstated dependencies in vignettes ... OK * checking package vignettes ... OK * checking running R code from vignettes ... SKIPPED * checking re-building of vignette outputs ... SKIPPED * checking PDF version of manual ... OK * DONE Status: 2 NOTEs See 'F:/biocbuild/bbs-3.19-bioc/meat/COTAN.Rcheck/00check.log' for details.
COTAN.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD INSTALL COTAN ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.19-bioc/R/library' * installing *source* package 'COTAN' ... ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading Note: ... may be used in an incorrect context ** 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 (COTAN)
COTAN.Rcheck/tests/outputTestDatasetCreation.Rout
R version 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup" Copyright (C) 2024 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. > > # Creates the files to be reloaded by the tests for comparisons > library(zeallot) > > outputTestDatasetCreation <- function(testsDir = file.path("tests", + "testthat")) { + utils::data("test.dataset", package = "COTAN") + options(parallelly.fork.enable = TRUE) + + obj <- COTAN(raw = test.dataset) + obj <- initializeMetaDataset(obj, GEO = " ", + sequencingMethod = "artificial", + sampleCondition = "test") + + obj <- proceedToCoex(obj, cores = 12L, saveObj = FALSE) + #saveRDS(obj, file = file.path(testsDir,"temp.RDS")) + + cell.names.test <- getCells(obj)[c(1L:10L, 591L:610L, 991L:1000L)] + genes.names.test <- getGenes(obj)[c(1L:10L, 291L:310L, 591L: 600L)] + saveRDS(cell.names.test, file.path(testsDir, "cell.names.test.RDS")) + saveRDS(genes.names.test, file.path(testsDir, "genes.names.test.RDS")) + + dispersion.test <- getDispersion(obj)[genes.names.test] + saveRDS(dispersion.test, file.path(testsDir, "dispersion.test.RDS")) + + raw.norm.test <- getNormalizedData(obj)[genes.names.test, cell.names.test] + saveRDS(raw.norm.test, file.path(testsDir, "raw.norm.test.RDS")) + + coex.test <- getGenesCoex(obj, genes = genes.names.test, zeroDiagonal = FALSE) + saveRDS(coex.test, file.path(testsDir, "coex.test.RDS")) + + lambda.test <- getLambda(obj)[genes.names.test] + saveRDS(lambda.test, file.path(testsDir, "lambda.test.RDS")) + + GDI.test <- calculateGDI(obj) + GDI.test <- GDI.test[genes.names.test, ] + saveRDS(GDI.test, file.path(testsDir, "GDI.test.RDS")) + + nu.test <- getNu(obj)[cell.names.test] + saveRDS(nu.test, file.path(testsDir, "nu.test.RDS")) + + pval.test <- calculatePValue(obj, geneSubsetCol = genes.names.test) + saveRDS(pval.test, file.path(testsDir, "pval.test.RDS")) + + GDIThreshold <- 1.46 + initialResolution <- 0.8 + + clusters <- cellsUniformClustering(obj, GDIThreshold = GDIThreshold, + initialResolution = initialResolution, + cores = 12L, saveObj = FALSE)[["clusters"]] + saveRDS(clusters, file.path(testsDir, "clusters1.RDS")) + + coexDF <- DEAOnClusters(obj, clusters = clusters, cores = 12L) + obj <- addClusterization(obj, clName = "clusters", + clusters = clusters, coexDF = coexDF) + + saveRDS(coexDF[genes.names.test, ], + file.path(testsDir, "coex.test.cluster1.RDS")) + + pvalDF <- pValueFromDEA(coexDF, getNumCells(obj), method = "none") + + saveRDS(pvalDF[genes.names.test, ], + file.path(testsDir, "pval.test.cluster1.RDS")) + + c(mergedClusters, mCoexDF) %<-% + mergeUniformCellsClusters(objCOTAN = obj, + clusters = NULL, + GDIThreshold = GDIThreshold, + cores = 12L, + distance = "cosine", + hclustMethod = "ward.D2", + saveObj = FALSE) + + saveRDS(mergedClusters[genes.names.test], + file.path(testsDir, "cluster_data_merged.RDS")) + } > > proc.time() user system elapsed 0.12 0.09 0.18
COTAN.Rcheck/tests/spelling.Rout
R version 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup" Copyright (C) 2024 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. > if (requireNamespace('spelling', quietly = TRUE)) + spelling::spell_check_test(vignettes = TRUE, error = FALSE, + skip_on_cran = TRUE) NULL > > proc.time() user system elapsed 0.18 0.01 0.21
COTAN.Rcheck/tests/testthat.Rout
R version 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup" Copyright (C) 2024 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. > Sys.setenv(R_TESTS = "") > library(testthat) > library(COTAN) > test_check("COTAN") Setting new log level to 3 Initializing `COTAN` meta-data Genes/cells selection done: dropped [0] genes and [0] cells Working on [10] genes and [20] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.9033203125 | max: 4.6796875 | % negative: 10 Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0.181818181818182 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Genes/cells selection done: dropped [0] genes and [0] cells Working on [10] genes and [20] cells Estimate dispersion: START Effective number of cores used: 1 Executing 4 genes batches from [1:2] to [7:8] Executing 1 genes batches from [9:10] to [9:10] Estimate dispersion: DONE dispersion | min: 0.9033203125 | max: 4.6796875 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 4 cells batches from [1:3] to [10:11] Executing 3 cells batches from [12:14] to [18:20] Estimate nu: DONE nu change (abs) | max: 1.75595238095238 | median: 1.07174634176587 | mean: 1.07174634176587 Estimate 'dispersion'/'nu': START Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 1.0362548828125 | max: 4.60986328125 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.0265938895089288 | median: 0.0144680038331048 | mean: 0.0144680038331048 Nu mean: 1.69633192486233 Marginal errors | max: 1.95570586131367 | median 1.32068160171502 | mean: 1.33375826507259 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.058837890625 | max: 3.528076171875 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.416683423613994 | median: 0.239880630367975 | mean: 0.239880630367975 Nu mean: 0.823197206753982 Marginal errors | max: 0.836359531101206 | median 0.703684202571891 | mean: 0.645537958989614 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.32879638671875 | max: 4.0302734375 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.164237872898673 | median: 0.0955985184389135 | mean: 0.0955985184389135 Nu mean: 1.06863935445976 Marginal errors | max: 0.259872988828242 | median 0.213703042752633 | mean: 0.197386407582083 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.2294921875 | max: 3.8720703125 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.055185575120883 | median: 0.0319991762044448 | mean: 0.0319991762044448 Nu mean: 0.976813601083562 Marginal errors | max: 0.0951586919577032 | median 0.079429703709466 | mean: 0.0724140148396648 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.2637939453125 | max: 3.929443359375 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.0196211148938294 | median: 0.01138609597457 | mean: 0.01138609597457 Nu mean: 1.00823501891926 Marginal errors | max: 0.0327747321002292 | median 0.0272104747849538 | mean: 0.0248963830312038 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.25177001953125 | max: 3.90966796875 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.00670099066960717 | median: 0.00388888266671264 | mean: 0.00388888266671264 Nu mean: 0.997187891997105 Marginal errors | max: 0.0114324509186883 | median 0.0094232649770607 | mean: 0.00863113610779571 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.25592041015625 | max: 3.91650390625 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.00230093811689414 | median: 0.00132529122122246 | mean: 0.00132529122122246 Nu mean: 1.00097564689567 Marginal errors | max: 0.00387133150664631 | median 0.0031091017608853 | mean: 0.00286071175800213 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.2545166015625 | max: 3.914306640625 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.000837011646904529 | median: 0.000470837393363011 | mean: 0.000470837393363011 Nu mean: 0.999633825746458 Marginal errors | max: 0.00122501723202006 | median 0.00102126435760308 | mean: 0.000943992659051318 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.2550048828125 | max: 3.9150390625 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.000209227351122054 | median: 0.000122070312500028 | mean: 0.000122070312500028 Nu mean: 1.00008715703862 Marginal errors | max: 0.000364602956581805 | median 0.000313956936819793 | mean: 0.000282899574318485 Estimate dispersion/nu: DONE Estimate 'dispersion'/'nu': START Initializing `COTAN` meta-data Genes/cells selection done: dropped [0] genes and [0] cells Working on [10] genes and [20] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.9033203125 | max: 4.6796875 | % negative: 10 Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0.181818181818182 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Calculate cells' coex: START Retrieving expected cells' contingency table calculating NN.. done calculating YN..NY..YY..t().. done Calculating cells' coex normalization factor Fraction of genes with very low expected contingency tables: 0 Retrieving observed cells' yes/yes contingency table calculating YY.. done Estimating cells' coex Calculate cells' coex: DONE Initializing `COTAN` meta-data Initializing `COTAN` meta-data Genes/cells selection done: dropped [0] genes and [0] cells Working on [10] genes and [20] cells Estimate 'dispersion'/'nu': START Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.903564453125 | max: 4.679443359375 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 1.75719246031746 | median: 1.07229953342014 | mean: 1.07229953342014 Nu mean: 1.68489292689732 Marginal errors | max: 1.73564890252257 | median 1.37996360874076 | mean: 1.32180348113228 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.0655517578125 | max: 3.5439453125 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.402649984216273 | median: 0.231868788425666 | mean: 0.231868788425666 Nu mean: 0.829218804209393 Marginal errors | max: 0.80321315986594 | median 0.677497553540581 | mean: 0.619375430892821 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.3260498046875 | max: 4.026123046875 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.158004893526231 | median: 0.0919692884670312 | mean: 0.0919692884670312 Nu mean: 1.0660356050592 Marginal errors | max: 0.250724014302326 | median 0.206232152124436 | mean: 0.190425623677198 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.23040771484375 | max: 3.8736572265625 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.0532774732102337 | median: 0.0308837890624999 | mean: 0.0308837890624999 Nu mean: 0.977606315852266 Marginal errors | max: 0.0916983669060123 | median 0.0765266929824948 | mean: 0.0697593208689684 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.26348876953125 | max: 3.928955078125 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.0189966206463044 | median: 0.0110199320575908 | mean: 0.0110199320575908 Nu mean: 1.00797668858871 Marginal errors | max: 0.0317151207459254 | median 0.0262702142278251 | mean: 0.0240886952086962 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.2518310546875 | max: 3.9097900390625 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.00670088501353994 | median: 0.00388888101583662 | mean: 0.00388888101583662 Nu mean: 0.997187996002297 Marginal errors | max: 0.0113693316356223 | median 0.00939669372836249 | mean: 0.00860715734056932 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.2559814453125 | max: 3.9166259765625 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.00251007446998996 | median: 0.00144735987374958 | mean: 0.00144735987374958 Nu mean: 1.00106271459624 Marginal errors | max: 0.00406746973787442 | median 0.00343393462175534 | mean: 0.00313496757119527 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.25445556640625 | max: 3.9140625 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.000837027590858019 | median: 0.000488281249999889 | mean: 0.000488281249999889 Nu mean: 0.999651253659142 Marginal errors | max: 0.00143433714371533 | median 0.00116636244706747 | mean: 0.00109289166947839 Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:10] to [1:10] Estimate dispersion: DONE dispersion | min: 0.2550048828125 | max: 3.9150390625 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 1 cells batches from [1:20] to [1:20] Estimate nu: DONE nu change (abs) | max: 0.000209227688885871 | median: 0.0001220703125 | mean: 0.0001220703125 Nu mean: 1.00008715737639 Marginal errors | max: 0.000379524846207957 | median 0.000325685250686547 | mean: 0.000295532844332236 Estimate dispersion/nu: DONE Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0.181818181818182 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Calculate cells' coex: START Retrieving expected cells' contingency table calculating NN.. done calculating YN..NY..YY..t().. done Calculating cells' coex normalization factor Fraction of genes with very low expected contingency tables: 0 Retrieving observed cells' yes/yes contingency table calculating YY.. done Estimating cells' coex Calculate cells' coex: DONE Calculate genes' partial coex: START Retrieving expected genes' partial contingency table calculating partial NN.. done calculating partial NY..YN..YY.. done Calculating genes' partial coex normalization factor Fraction of genes with very low expected contingency tables: 0.325 Retrieving observed genes' yes/yes partial contingency table calculating partial YY.. done Estimating genes' partial coex Calculate genes' partial coex: DONE Calculate cells' partial coex: START Retrieving expected cells' partial contingency table calculating partial NN.. done calculating partial YN..NY..YY.. done Calculating cells' partial coex normalization factor Fraction of genes with very low expected contingency tables: 0 Retrieving observed cells' yes/yes partial contingency table calculating partial YY.. done Estimating cells' partial coex Calculate cells' partial coex: DONE Asked to drop 2 genes and 0 cells Asked to drop 0 genes and 4 cells Asked to drop 2 genes and 2 cells Attaching package: 'rlang' The following objects are masked from 'package:testthat': is_false, is_null, is_true Genes/cells selection done: dropped [0] genes and [0] cells Working on [10] genes and [20] cells calculating YY.. done calculating YY.. done calculating YN..NY..NN..t().. done Estimate dispersion: START Effective number of cores used: 1 Executing 3 genes batches from [1:3] to [8:10] Estimate dispersion: DONE dispersion | min: 0.9033203125 | max: 4.6796875 | % negative: 10 calculating NN.. done calculating NN.. done calculating NY..YN..YY..t().. done Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0.181818181818182 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Calculate genes' partial coex: START Retrieving expected genes' partial contingency table calculating partial NN.. done calculating partial NY..YN..YY.. done Calculating genes' partial coex normalization factor Fraction of genes with very low expected contingency tables: 0.1 Retrieving observed genes' yes/yes partial contingency table calculating partial YY.. done Estimating genes' partial coex Calculate genes' partial coex: DONE Calculate genes' partial coex: START Retrieving expected genes' partial contingency table calculating partial NN.. done calculating partial NY..YN..YY.. done Calculating genes' partial coex normalization factor Fraction of genes with very low expected contingency tables: 0.4 Retrieving observed genes' yes/yes partial contingency table calculating partial YY.. done Estimating genes' partial coex Calculate genes' partial coex: DONE Genes/cells selection done: dropped [0] genes and [0] cells Working on [10] genes and [20] cells calculating YY.. done calculating YY.. done calculating NY..YN..NN..t().. done Estimate 'dispersion'/'nu': START Estimate dispersion: START Effective number of cores used: 1 Executing 3 genes batches from [1:3] to [8:10] Estimate dispersion: DONE dispersion | min: 0.903564453125 | max: 4.679443359375 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 4 cells batches from [1:4] to [13:16] Executing 1 cells batches from [17:20] to [17:20] Estimate nu: DONE nu change (abs) | max: 1.75719246031746 | median: 1.07229953342014 | mean: 1.07229953342014 Nu mean: 1.68489292689732 Marginal errors | max: 0.25535328937316 | median 0.0807577993228135 | mean: 0.101980750205762 Estimate dispersion: START Effective number of cores used: 1 Executing 3 genes batches from [1:3] to [8:10] Estimate dispersion: DONE dispersion | min: 1.037109375 | max: 4.6107177734375 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 4 cells batches from [1:4] to [13:16] Executing 1 cells batches from [17:20] to [17:20] Estimate nu: DONE nu change (abs) | max: 0.0273438105507502 | median: 0.0148852611818011 | mean: 0.0148852611818011 Nu mean: 1.69735147626627 Marginal errors | max: 0.00326864580272002 | median 0.00111524657842743 | mean: 0.00131556083122533 Estimate dispersion: START Effective number of cores used: 1 Executing 3 genes batches from [1:3] to [8:10] Estimate dispersion: DONE dispersion | min: 1.03887939453125 | max: 4.6097412109375 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 4 cells batches from [1:4] to [13:16] Executing 1 cells batches from [17:20] to [17:20] Estimate nu: DONE nu change (abs) | max: 0 | median: 0 | mean: 0 Nu mean: 1.69735147626627 Marginal errors | max: 7.56328383637594e-05 | median 1.72948087246994e-05 | mean: 2.99252342145451e-05 Estimate dispersion/nu: DONE calculating NN.. done calculating NN.. done calculating YN..NY..YY..t().. done Calculate cells' coex: START Retrieving expected cells' contingency table calculating NN.. done calculating YN..NY..YY..t().. done Calculating cells' coex normalization factor Fraction of genes with very low expected contingency tables: 0 Retrieving observed cells' yes/yes contingency table calculating YY.. done Estimating cells' coex Calculate cells' coex: DONE Calculate cells' partial coex: START Retrieving expected cells' partial contingency table calculating partial NN.. done calculating partial YN..NY..YY.. done Calculating cells' partial coex normalization factor Fraction of genes with very low expected contingency tables: 0 Retrieving observed cells' yes/yes partial contingency table calculating partial YY.. done Estimating cells' partial coex Calculate cells' partial coex: DONE Calculate cells' partial coex: START Retrieving expected cells' partial contingency table calculating partial NN.. done calculating partial YN..NY..YY.. done Calculating cells' partial coex normalization factor Fraction of genes with very low expected contingency tables: 0 Retrieving observed cells' yes/yes partial contingency table calculating partial YY.. done Estimating cells' partial coex Calculate cells' partial coex: DONE Genes/cells selection done: dropped [0] genes and [0] cells Working on [10] genes and [20] cells Estimate 'dispersion'/'nu': START Estimate dispersion: START Effective number of cores used: 1 Executing 3 genes batches from [1:3] to [8:10] Estimate dispersion: DONE dispersion | min: 0.903564453125 | max: 4.679443359375 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 4 cells batches from [1:4] to [13:16] Executing 1 cells batches from [17:20] to [17:20] Estimate nu: DONE nu change (abs) | max: 1.75719246031746 | median: 1.07229953342014 | mean: 1.07229953342014 Nu mean: 1.68489292689732 Marginal errors | max: 0.25535328937316 | median 0.0807577993228135 | mean: 0.101980750205762 Estimate dispersion: START Effective number of cores used: 1 Executing 3 genes batches from [1:3] to [8:10] Estimate dispersion: DONE dispersion | min: 1.037109375 | max: 4.6107177734375 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 4 cells batches from [1:4] to [13:16] Executing 1 cells batches from [17:20] to [17:20] Estimate nu: DONE nu change (abs) | max: 0.0273438105507502 | median: 0.0148852611818011 | mean: 0.0148852611818011 Nu mean: 1.69735147626627 Marginal errors | max: 0.00326864580272002 | median 0.00111524657842743 | mean: 0.00131556083122533 Estimate dispersion: START Effective number of cores used: 1 Executing 3 genes batches from [1:3] to [8:10] Estimate dispersion: DONE dispersion | min: 1.03887939453125 | max: 4.6097412109375 | % negative: 10 Estimate nu: START Effective number of cores used: 1 Executing 4 cells batches from [1:4] to [13:16] Executing 1 cells batches from [17:20] to [17:20] Estimate nu: DONE nu change (abs) | max: 0 | median: 0 | mean: 0 Nu mean: 1.69735147626627 Marginal errors | max: 7.56328383637594e-05 | median 1.72948087246994e-05 | mean: 2.99252342145451e-05 Estimate dispersion/nu: DONE Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0.181818181818182 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Calculating S: START Calculating S: DONE Calculating G: START calculating YY.. done calculating YN..NY..NN..t().. done calculating NN.. done calculating NY..YN..YY..t().. done Estimating G Calculating G: DONE Using S Calculating S: START Calculating S: DONE calculating PValues: START Get p-values genome wide on columns and genome wide on rows calculating PValues: DONE Using G Calculating G: START calculating YY.. done calculating YN..NY..NN..t().. done calculating NN.. done calculating NY..YN..YY..t().. done Estimating G Calculating G: DONE calculating PValues: START Get p-values on a set of genes on columns and on a set of genes on rows calculating PValues: DONE Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE Calculate GDI dataframe: START Using G Calculating G: START calculating YY.. done calculating YN..NY..NN..t().. done calculating NN.. done calculating NY..YN..YY..t().. done Estimating G Calculating G: DONE S matrix sorted Calculate GDI dataframe: DONE Calculating S: START Calculating S: DONE S matrix sorted S matrix sorted Initializing `COTAN` meta-data Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [1200] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: 0.2197265625 | max: 6.08056640625 | % negative: 0 Only analysis time 0.0759463469187419 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.122860817114512 Total time 0.210409533977509 Initializing `COTAN` meta-data Condition test n cells 1200 Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [1200] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: 0.2197265625 | max: 6.08056640625 | % negative: 0 Only analysis time 0.0760177334149679 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.11990034977595 Total time 0.207383465766907 Using S Calculating S: START Calculating S: DONE calculating PValues: START Get p-values on a set of genes on columns and genome wide on rows calculating PValues: DONE Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE Initializing `COTAN` meta-data Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [1200] cells PCA: START PCA: DONE Hierarchical clustering: START Hierarchical clustering: DONE Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: 0.2197265625 | max: 6.08056640625 | % negative: 0 Cotan genes' coex estimation not requested Total time 0.169109447797139 Saving elaborated data locally at: F:\biocbuild\bbs-3.19-bioc\tmpdir\RtmpOQzPyW/test.cotan.RDS Creating cells' uniform clustering: START In iteration 1 the number of cells to re-cluster is 1200 cells belonging to 0 clusters Creating Seurat object: START Normalizing layer: counts Performing log-normalization 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Finding variable features for layer counts Calculating gene variances 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Calculating feature variances of standardized and clipped values 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Centering and scaling data matrix | | | 0% | |======================================================================| 100% PC_ 1 Positive: g-000558, g-000570, g-000499, g-000504, g-000546, g-000506, g-000503, g-000517, g-000596, g-000528 g-000527, g-000580, g-000592, g-000578, g-000509, g-000488, g-000555, g-000577, g-000534, g-000583 g-000598, g-000535, g-000512, g-000554, g-000519, g-000525, g-000548, g-000544, g-000502, g-000541 Negative: g-000133, g-000007, g-000074, g-000141, g-000057, g-000235, g-000170, g-000019, g-000195, g-000140 g-000183, g-000031, g-000046, g-000178, g-000177, g-000161, g-000157, g-000139, g-000011, g-000135 g-000125, g-000208, g-000061, g-000085, g-000204, g-000104, g-000237, g-000004, g-000038, g-000128 PC_ 2 Positive: g-000039, g-000050, g-000175, g-000078, g-000116, g-000189, g-000135, g-000047, g-000072, g-000087 g-000063, g-000235, g-000066, g-000109, g-000018, g-000074, g-000231, g-000136, g-000034, g-000207 g-000128, g-000167, g-000171, g-000049, g-000182, g-000013, g-000054, g-000062, g-000240, g-000158 Negative: g-000584, g-000583, g-000544, g-000519, g-000575, g-000516, g-000585, g-000486, g-000489, g-000539 g-000484, g-000502, g-000523, g-000595, g-000305, g-000574, g-000599, g-000589, g-000509, g-000538 g-000526, g-000551, g-000579, g-000590, g-000445, g-000556, g-000543, g-000501, g-000504, g-000570 PC_ 3 Positive: g-000015, g-000575, g-000483, g-000316, g-000025, g-000364, g-000050, g-000278, g-000443, g-000360 g-000332, g-000124, g-000212, g-000387, g-000536, g-000252, g-000251, g-000321, g-000501, g-000470 g-000582, g-000106, g-000455, g-000368, g-000081, g-000104, g-000437, g-000288, g-000386, g-000317 Negative: g-000211, g-000337, g-000129, g-000185, g-000397, g-000403, g-000253, g-000098, g-000390, g-000303 g-000052, g-000088, g-000463, g-000468, g-000236, g-000209, g-000005, g-000375, g-000342, g-000262 g-000388, g-000091, g-000413, g-000285, g-000003, g-000095, g-000142, g-000205, g-000432, g-000241 PC_ 4 Positive: g-000379, g-000193, g-000212, g-000434, g-000593, g-000513, g-000177, g-000223, g-000069, g-000131 g-000162, g-000345, g-000462, g-000484, g-000448, g-000229, g-000365, g-000302, g-000010, g-000366 g-000051, g-000535, g-000269, g-000270, g-000155, g-000529, g-000373, g-000008, g-000393, g-000306 Negative: g-000334, g-000398, g-000292, g-000095, g-000097, g-000202, g-000382, g-000195, g-000007, g-000079 g-000086, g-000240, g-000263, g-000317, g-000576, g-000557, g-000160, g-000154, g-000214, g-000228 g-000313, g-000053, g-000524, g-000374, g-000568, g-000188, g-000358, g-000528, g-000362, g-000150 PC_ 5 Positive: g-000451, g-000339, g-000295, g-000328, g-000544, g-000061, g-000227, g-000391, g-000556, g-000237 g-000067, g-000165, g-000449, g-000591, g-000087, g-000129, g-000197, g-000203, g-000487, g-000505 g-000333, g-000029, g-000271, g-000064, g-000583, g-000156, g-000448, g-000153, g-000526, g-000393 Negative: g-000518, g-000108, g-000186, g-000170, g-000401, g-000337, g-000047, g-000599, g-000432, g-000578 g-000042, g-000065, g-000493, g-000261, g-000533, g-000256, g-000560, g-000596, g-000368, g-000381 g-000535, g-000338, g-000215, g-000159, g-000365, g-000234, g-000173, g-000387, g-000225, g-000272 Computing nearest neighbor graph Computing SNN Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck Number of nodes: 1200 Number of edges: 55489 Running Louvain algorithm with multilevel refinement... 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Maximum modularity in 10 random starts: 0.5973 Number of communities: 4 Elapsed time: 0 seconds Used resolution for Seurat clusterization is: 0.8 00:51:48 UMAP embedding parameters a = 0.9922 b = 1.112 00:51:48 Read 1200 rows and found 50 numeric columns 00:51:48 Using Annoy for neighbor search, n_neighbors = 30 00:51:48 Building Annoy index with metric = cosine, n_trees = 50 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| 00:51:48 Writing NN index file to temp file F:\biocbuild\bbs-3.19-bioc\tmpdir\RtmpOQzPyW\file4b7034ba7bbc 00:51:48 Searching Annoy index using 1 thread, search_k = 3000 00:51:48 Annoy recall = 100% 00:51:49 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30 00:51:51 Initializing from normalized Laplacian + noise (using RSpectra) 00:51:51 Commencing optimization for 500 epochs, with 42270 positive edges Using method 'umap' 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| 00:51:55 Optimization finished Creating PDF UMAP in file: F:\biocbuild\bbs-3.19-bioc\tmpdir\RtmpOQzPyW/test/reclustering/pdf_umap_1.pdf Creating Seurat object: DONE * checking uniformity of cluster '0' of 4 clusters Asked to drop 0 genes and 847 cells Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [353] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: -0.038818359375 | max: 11.109375 | % negative: 5 Only analysis time 0.0539694666862488 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0.000521353300055463 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.120393252372742 Total time 0.18827953338623 Checking uniformity for the cluster '01_0000' with 353 cells Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE GDI plot Removed 0 low GDI genes (such as the fully-expressed) in GDI plot Cluster 01_0000 is uniform 0.83% of the genes is above the given GDI threshold 1.46 GDI 99% quantile is at 1.4439 cluster 01_0000 is uniform * checking uniformity of cluster '1' of 4 clusters Asked to drop 0 genes and 879 cells Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [321] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: -0.0501708984375 | max: 14.515625 | % negative: 8.5 Only analysis time 0.0523530006408691 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0.00168053244592346 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.123947099844615 Total time 0.190086483955383 Checking uniformity for the cluster '01_0001' with 321 cells Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE GDI plot Removed 0 low GDI genes (such as the fully-expressed) in GDI plot Cluster 01_0001 is uniform 0.5% of the genes is above the given GDI threshold 1.46 GDI 99% quantile is at 1.4305 cluster 01_0001 is uniform * checking uniformity of cluster '2' of 4 clusters Asked to drop 0 genes and 905 cells Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [295] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: -0.054443359375 | max: 104 | % negative: 36.5 Only analysis time 0.0490442832310994 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0.35504159733777 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.122907634576162 Total time 0.184921483198802 Checking uniformity for the cluster '01_0002' with 295 cells Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE GDI plot Removed 0 low GDI genes (such as the fully-expressed) in GDI plot Cluster 01_0002 is uniform 0% of the genes is above the given GDI threshold 1.46 GDI 99% quantile is at 1.3925 cluster 01_0002 is uniform * checking uniformity of cluster '3' of 4 clusters Asked to drop 0 genes and 969 cells Cotan analysis functions started Asked to drop 1 genes and 0 cells Genes/cells selection done: dropped [1] genes and [0] cells Working on [599] genes and [231] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:599] to [1:599] Estimate dispersion: DONE dispersion | min: -0.0662841796875 | max: 82.5 | % negative: 33.889816360601 Only analysis time 0.046078097820282 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0.318091263216472 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.117520685990651 Total time 0.178202199935913 Checking uniformity for the cluster '01_0003' with 231 cells Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE GDI plot Removed 0 low GDI genes (such as the fully-expressed) in GDI plot Cluster 01_0003 is uniform 0% of the genes is above the given GDI threshold 1.46 GDI 99% quantile is at 1.373 cluster 01_0003 is uniform Found 4 uniform and 0 non-uniform clusters NO new possible uniform clusters! Unclustered cell left: 0 The final raw clusterization contains [ 4 ] different clusters: 01_0000, 01_0001, 01_0002, 01_0003 Differential Expression Analysis - START Effective number of cores used: 1 * DEA on cluster '1' * DEA on cluster '2' * DEA on cluster '3' * DEA on cluster '4' Differential Expression Analysis - DONE Applied reordering to clusterization is: 1 -> 3, 2 -> 1, 3 -> 2, 4 -> 4 Cluster, UMAP and Saving the Seurat dataset Computing nearest neighbor graph Computing SNN Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck Number of nodes: 1200 Number of edges: 55489 Running Louvain algorithm with multilevel refinement... 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Maximum modularity in 10 random starts: 0.6846 Number of communities: 4 Elapsed time: 0 seconds 00:53:06 UMAP embedding parameters a = 0.9922 b = 1.112 00:53:06 Read 1200 rows and found 25 numeric columns 00:53:06 Using Annoy for neighbor search, n_neighbors = 30 00:53:06 Building Annoy index with metric = cosine, n_trees = 50 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| 00:53:06 Writing NN index file to temp file F:\biocbuild\bbs-3.19-bioc\tmpdir\RtmpOQzPyW\file4b701f801d33 00:53:06 Searching Annoy index using 1 thread, search_k = 3000 00:53:06 Annoy recall = 100% 00:53:07 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30 00:53:08 Initializing from normalized Laplacian + noise (using RSpectra) 00:53:08 Commencing optimization for 500 epochs, with 43428 positive edges Using method 'umap' 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| 00:53:13 Optimization finished Creating cells' uniform clustering: DONE Differential Expression Analysis - START Effective number of cores used: 1 * DEA on cluster '1' * DEA on cluster '2' * DEA on cluster '3' * DEA on cluster '4' Differential Expression Analysis - DONE Applied reordering to clusterization is: 1 -> 1, 2 -> 2, 3 -> 3, 4 -> 4 Asked to drop 0 genes and 905 cells Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [295] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: -0.054443359375 | max: 104 | % negative: 36.5 Only analysis time 0.0466991186141968 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0.35504159733777 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.12164294719696 Total time 0.180991299947103 Checking uniformity for the cluster 'Cluster_2' with 295 cells Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE GDI plot Removed 0 low GDI genes (such as the fully-expressed) in GDI plot Cluster Cluster_2 is uniform 0% of the genes is above the given GDI threshold 1.46 GDI 99% quantile is at 1.3925 Differential Expression Analysis - START Effective number of cores used: 1 * DEA on cluster '1' * DEA on cluster '2' * DEA on cluster '3' * DEA on cluster '4' * DEA on cluster '-1' Differential Expression Analysis - DONE Applied reordering to clusterization is: 1 -> 2, 2 -> 1, 3 -> 4, 4 -> 3, -1 -> -1 Applied reordering to clusterization is: 1 -> 2, 2 -> 3, 3 -> 1, 4 -> 4, -1 -> -1 Creating cells' uniform clustering: START In iteration 1 the number of cells to re-cluster is 1200 cells belonging to 0 clusters Creating Seurat object: START Normalizing layer: counts Performing log-normalization 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Finding variable features for layer counts Calculating gene variances 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Calculating feature variances of standardized and clipped values 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Centering and scaling data matrix | | | 0% | |======================================================================| 100% PC_ 1 Positive: g-000558, g-000570, g-000499, g-000504, g-000546, g-000506, g-000503, g-000517, g-000596, g-000528 g-000527, g-000580, g-000592, g-000578, g-000509, g-000488, g-000555, g-000577, g-000534, g-000583 g-000598, g-000535, g-000512, g-000554, g-000519, g-000525, g-000548, g-000544, g-000502, g-000541 Negative: g-000133, g-000007, g-000074, g-000141, g-000057, g-000235, g-000170, g-000019, g-000195, g-000140 g-000183, g-000031, g-000046, g-000178, g-000177, g-000161, g-000157, g-000139, g-000011, g-000135 g-000125, g-000208, g-000061, g-000085, g-000204, g-000104, g-000237, g-000004, g-000038, g-000128 PC_ 2 Positive: g-000039, g-000050, g-000175, g-000078, g-000116, g-000189, g-000135, g-000047, g-000072, g-000087 g-000063, g-000235, g-000066, g-000109, g-000018, g-000074, g-000231, g-000136, g-000034, g-000207 g-000128, g-000167, g-000171, g-000049, g-000182, g-000013, g-000054, g-000062, g-000240, g-000158 Negative: g-000584, g-000583, g-000544, g-000519, g-000575, g-000516, g-000585, g-000486, g-000489, g-000539 g-000484, g-000502, g-000523, g-000595, g-000305, g-000574, g-000599, g-000589, g-000509, g-000538 g-000526, g-000551, g-000579, g-000590, g-000445, g-000556, g-000543, g-000501, g-000504, g-000570 PC_ 3 Positive: g-000015, g-000575, g-000483, g-000316, g-000025, g-000364, g-000050, g-000278, g-000443, g-000360 g-000332, g-000124, g-000212, g-000387, g-000536, g-000252, g-000251, g-000321, g-000501, g-000470 g-000582, g-000106, g-000455, g-000368, g-000081, g-000104, g-000437, g-000288, g-000386, g-000317 Negative: g-000211, g-000337, g-000129, g-000185, g-000397, g-000403, g-000253, g-000098, g-000390, g-000303 g-000052, g-000088, g-000463, g-000468, g-000236, g-000209, g-000005, g-000375, g-000342, g-000262 g-000388, g-000091, g-000413, g-000285, g-000003, g-000095, g-000142, g-000205, g-000432, g-000241 PC_ 4 Positive: g-000379, g-000193, g-000212, g-000434, g-000593, g-000513, g-000177, g-000223, g-000069, g-000131 g-000162, g-000345, g-000462, g-000484, g-000448, g-000229, g-000365, g-000302, g-000010, g-000366 g-000051, g-000535, g-000269, g-000270, g-000155, g-000529, g-000373, g-000008, g-000393, g-000306 Negative: g-000334, g-000398, g-000292, g-000095, g-000097, g-000202, g-000382, g-000195, g-000007, g-000079 g-000086, g-000240, g-000263, g-000317, g-000576, g-000557, g-000160, g-000154, g-000214, g-000228 g-000313, g-000053, g-000524, g-000374, g-000568, g-000188, g-000358, g-000528, g-000362, g-000150 PC_ 5 Positive: g-000451, g-000339, g-000295, g-000328, g-000544, g-000061, g-000227, g-000391, g-000556, g-000237 g-000067, g-000165, g-000449, g-000591, g-000087, g-000129, g-000197, g-000203, g-000487, g-000505 g-000333, g-000029, g-000271, g-000064, g-000583, g-000156, g-000448, g-000153, g-000526, g-000393 Negative: g-000518, g-000108, g-000186, g-000170, g-000401, g-000337, g-000047, g-000599, g-000432, g-000578 g-000042, g-000065, g-000493, g-000261, g-000533, g-000256, g-000560, g-000596, g-000368, g-000381 g-000535, g-000338, g-000215, g-000159, g-000365, g-000234, g-000173, g-000387, g-000225, g-000272 Computing nearest neighbor graph Computing SNN Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck Number of nodes: 1200 Number of edges: 55489 Running Louvain algorithm with multilevel refinement... 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Maximum modularity in 10 random starts: 0.5973 Number of communities: 4 Elapsed time: 0 seconds Used resolution for Seurat clusterization is: 0.8 00:53:34 UMAP embedding parameters a = 0.9922 b = 1.112 00:53:34 Read 1200 rows and found 50 numeric columns 00:53:34 Using Annoy for neighbor search, n_neighbors = 30 00:53:34 Building Annoy index with metric = cosine, n_trees = 50 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| 00:53:34 Writing NN index file to temp file F:\biocbuild\bbs-3.19-bioc\tmpdir\RtmpOQzPyW\file4b7077e3785c 00:53:34 Searching Annoy index using 1 thread, search_k = 3000 00:53:34 Annoy recall = 100% 00:53:35 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30 00:53:37 Initializing from normalized Laplacian + noise (using RSpectra) 00:53:37 Commencing optimization for 500 epochs, with 42270 positive edges Using method 'umap' 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| 00:53:42 Optimization finished Creating PDF UMAP in file: F:\biocbuild\bbs-3.19-bioc\tmpdir\RtmpOQzPyW/test/reclustering/pdf_umap_1.pdf Creating Seurat object: DONE Using passed in clusterization * checking uniformity of cluster '1' of 2 clusters Asked to drop 0 genes and 600 cells Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [600] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: -0.0386962890625 | max: 19.40625 | % negative: 6.5 Only analysis time 0.0571195522944132 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0.000110926234054354 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.125938248634338 Total time 0.195152533054352 Checking uniformity for the cluster '01_0001' with 600 cells Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE GDI plot Removed 0 low GDI genes (such as the fully-expressed) in GDI plot Cluster 01_0001 is uniform 1% of the genes is above the given GDI threshold 1.46 GDI 99% quantile is at 1.4534 cluster 01_0001 is uniform * checking uniformity of cluster '2' of 2 clusters Asked to drop 0 genes and 600 cells Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [600] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: -0.032958984375 | max: 10.0859375 | % negative: 3.66666666666667 Only analysis time 0.0568965156873067 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 6.10094287298946e-05 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.13107176621755 Total time 0.20047234694163 Checking uniformity for the cluster '01_0002' with 600 cells Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE GDI plot Removed 0 low GDI genes (such as the fully-expressed) in GDI plot Cluster 01_0002 is uniform 0.5% of the genes is above the given GDI threshold 1.46 GDI 99% quantile is at 1.4378 cluster 01_0002 is uniform Found 2 uniform and 0 non-uniform clusters NO new possible uniform clusters! Unclustered cell left: 0 The final raw clusterization contains [ 2 ] different clusters: 01_0001, 01_0002 Differential Expression Analysis - START Effective number of cores used: 1 * DEA on cluster '1' * DEA on cluster '2' Differential Expression Analysis - DONE Applied reordering to clusterization is: 1 -> 1, 2 -> 2 Cluster, UMAP and Saving the Seurat dataset Computing nearest neighbor graph Computing SNN Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck Number of nodes: 1200 Number of edges: 55489 Running Louvain algorithm with multilevel refinement... 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| Maximum modularity in 10 random starts: 0.6846 Number of communities: 4 Elapsed time: 0 seconds 00:54:20 UMAP embedding parameters a = 0.9922 b = 1.112 00:54:20 Read 1200 rows and found 25 numeric columns 00:54:20 Using Annoy for neighbor search, n_neighbors = 30 00:54:20 Building Annoy index with metric = cosine, n_trees = 50 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| 00:54:20 Writing NN index file to temp file F:\biocbuild\bbs-3.19-bioc\tmpdir\RtmpOQzPyW\file4b705e896127 00:54:20 Searching Annoy index using 1 thread, search_k = 3000 00:54:20 Annoy recall = 100% 00:54:21 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30 00:54:22 Initializing from normalized Laplacian + noise (using RSpectra) 00:54:22 Commencing optimization for 500 epochs, with 43428 positive edges Using method 'umap' 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **************************************************| 00:54:27 Optimization finished Creating cells' uniform clustering: DONE findClustersMarkers - START Differential Expression Analysis - START Effective number of cores used: 1 * DEA on cluster '1' * DEA on cluster '2' * DEA on cluster '3' * DEA on cluster '4' Differential Expression Analysis - DONE clustersDeltaExpression - START Handling cluster '1' with mean UDE 1.20998115359079 Handling cluster '2' with mean UDE 0.538244816501366 Handling cluster '3' with mean UDE 1.43530796540674 Handling cluster '4' with mean UDE 0.632684489354434 clustersDeltaExpression - DONE Log Fold Change Analysis - START * Analysis of cluster: '1' * Analysis of cluster: '2' * Analysis of cluster: '3' * Analysis of cluster: '4' Log Fold Change Analysis - DONE findClustersMarkers - DONE findClustersMarkers - START Differential Expression Analysis - START Effective number of cores used: 1 * DEA on cluster '1' * DEA on cluster '2' * DEA on cluster '3' * DEA on cluster '4' Differential Expression Analysis - DONE clustersDeltaExpression - START Handling cluster '1' with mean UDE 1.20998115359079 Handling cluster '2' with mean UDE 0.538244816501366 Handling cluster '3' with mean UDE 1.43530796540674 Handling cluster '4' with mean UDE 0.632684489354434 clustersDeltaExpression - DONE Log Fold Change Analysis - START * Analysis of cluster: '1' * Analysis of cluster: '2' * Analysis of cluster: '3' * Analysis of cluster: '4' Log Fold Change Analysis - DONE findClustersMarkers - DONE findClustersMarkers - START Differential Expression Analysis - START Effective number of cores used: 1 * DEA on cluster '1' * DEA on cluster '2' * DEA on cluster '3' * DEA on cluster '4' Differential Expression Analysis - DONE clustersDeltaExpression - START Handling cluster '1' with mean UDE 1.20998115359079 Handling cluster '2' with mean UDE 0.538244816501366 Handling cluster '3' with mean UDE 1.43530796540674 Handling cluster '4' with mean UDE 0.632684489354434 clustersDeltaExpression - DONE Log Fold Change Analysis - START * Analysis of cluster: '1' * Analysis of cluster: '2' * Analysis of cluster: '3' * Analysis of cluster: '4' Log Fold Change Analysis - DONE findClustersMarkers - DONE [1] "1" Asked to drop 0 genes and 879 cells Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [321] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: -0.0501708984375 | max: 14.515625 | % negative: 8.5 Only analysis time 0.0468816161155701 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0.00168053244592346 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.127562503019969 Total time 0.187931168079376 Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE [1] "3" Asked to drop 0 genes and 847 cells Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [353] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: -0.038818359375 | max: 11.109375 | % negative: 5 Only analysis time 0.0516011317571004 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0.000521353300055463 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.120697935422262 Total time 0.185402552286784 Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE Genes/cells selection done: dropped [0] genes and [0] cells Working on [10] genes and [20] cells Initializing `COTAN` meta-data Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [1200] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: 0.2197265625 | max: 6.08056640625 | % negative: 0 Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [1200] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: 0.2197265625 | max: 6.08056640625 | % negative: 0 Only analysis time 0.0813351988792419 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.132704118887583 Total time 0.22769676844279 Calculating gene co-expression space - START Using S Calculating S: START Calculating S: DONE calculating PValues: START Get p-values on a set of genes on columns and genome wide on rows calculating PValues: DONE Number of selected secondary markers: 109 Calculating S: START Calculating S: DONE S matrix sorted Number of columns (V set - secondary markers): 109 Number of rows (U set): 60 Calculating gene co-expression space - DONE Establishing gene clusters - START Calculating gene co-expression space - START Using S Calculating S: START Calculating S: DONE calculating PValues: START Get p-values on a set of genes on columns and genome wide on rows calculating PValues: DONE Number of selected secondary markers: 109 Calculating S: START Calculating S: DONE S matrix sorted Number of columns (V set - secondary markers): 109 Number of rows (U set): 60 Calculating gene co-expression space - DONE Establishing gene clusters - DONE Initializing `COTAN` meta-data Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [1200] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: 0.2197265625 | max: 6.08056640625 | % negative: 0 Cotan genes' coex estimation not requested Total time 0.10625760157903 Differential Expression Analysis - START Effective number of cores used: 1 * DEA on cluster '1' * DEA on cluster '2' * DEA on cluster '3' * DEA on cluster '4' Differential Expression Analysis - DONE Log Fold Change Analysis - START * Analysis of cluster: '1' * Analysis of cluster: '2' * Analysis of cluster: '3' * Analysis of cluster: '4' Log Fold Change Analysis - DONE clustersDeltaExpression - START Handling cluster '1' with mean UDE 1.43530796540674 Handling cluster '2' with mean UDE 0.640931107489519 Handling cluster '3' with mean UDE 0.546546914955575 Handling cluster '4' with mean UDE 1.22034802329657 clustersDeltaExpression - DONE In group G1 there are 3 detected over 3 genes In group G2 there are 2 detected over 2 genes In group G3 there are 5 detected over 5 genes Merging cells' uniform clustering: START Start merging nearest clusters: iteration 1 Differential Expression Analysis - START Effective number of cores used: 1 * DEA on cluster '1' * DEA on cluster '2' * DEA on cluster '3' * DEA on cluster '4' Differential Expression Analysis - DONE Clusters pairs for merging: c("1", "2") c("3", "4") c("2", "3") c("2", "4") c("1", "3") c("1", "4") *1_2-merge Asked to drop 0 genes and 626 cells Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [574] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: -0.0340576171875 | max: 10.4375 | % negative: 4.33333333333333 Only analysis time 0.0559033830960592 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0.000105379922351636 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.121630903085073 Total time 0.190772585074107 Checking uniformity for the cluster '1_2-merge' with 574 cells Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE GDI plot Removed 0 low GDI genes (such as the fully-expressed) in GDI plot Cluster 1_2-merge is uniform 0.67% of the genes is above the given GDI threshold 1.46 GDI 99% quantile is at 1.4297 Clusters 1 and 2 can be merged *3_4-merge Asked to drop 0 genes and 574 cells Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [626] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: -0.03839111328125 | max: 17.40625 | % negative: 6.66666666666667 Only analysis time 0.0574844797452291 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 5.54631170271769e-05 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.128111100196838 Total time 0.198543465137482 Checking uniformity for the cluster '3_4-merge' with 626 cells Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE GDI plot Removed 0 low GDI genes (such as the fully-expressed) in GDI plot Cluster 3_4-merge is uniform 1% of the genes is above the given GDI threshold 1.46 GDI 99% quantile is at 1.4544 Clusters 3 and 4 can be merged *Clusters 2 or 3 is now missing due to previous merges: skip. *Clusters 2 or 4 is now missing due to previous merges: skip. *Clusters 1 or 3 is now missing due to previous merges: skip. *Clusters 1 or 4 is now missing due to previous merges: skip. Executed 2 merges out of 6 Start merging nearest clusters: iteration 2 Differential Expression Analysis - START Effective number of cores used: 1 * DEA on cluster '1_2-merge' * DEA on cluster '3_4-merge' Differential Expression Analysis - DONE Clusters pairs for merging: c("1_2-merge", "3_4-merge") *1_2-merge_3_4-merge-merge Asked to drop no genes or cells Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [1200] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: 0.2197265625 | max: 6.08056640625 | % negative: 0 Only analysis time 0.0759613196055094 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.127670081456502 Total time 0.21656133333842 Checking uniformity for the cluster '1_2-merge_3_4-merge-merge' with 1200 cells Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE GDI plot Removed 0 low GDI genes (such as the fully-expressed) in GDI plot Cluster 1_2-merge_3_4-merge-merge is not uniform 22.17% of the genes is above the given GDI threshold 1.46 GDI 99% quantile is at 1.6405 Merging clusters 1_2-merge and 3_4-merge results in a too high GDI None of the 1 nearest cluster pairs could be merged The final merged clusterization contains [2] different clusters: 1_2-merge, 3_4-merge Differential Expression Analysis - START Effective number of cores used: 1 * DEA on cluster '1' * DEA on cluster '2' Differential Expression Analysis - DONE Applied reordering to clusterization is: 1 -> 1, 2 -> 2 Merging cells' uniform clustering: DONE Applied reordering to clusterization is: 1 -> 1, 2 -> 2 Log Fold Change Analysis - START * Analysis of cluster: '1' * Analysis of cluster: '2' Log Fold Change Analysis - DONE Asked to drop 0 genes and 626 cells Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [574] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: -0.0340576171875 | max: 10.4375 | % negative: 4.33333333333333 Only analysis time 0.0590692162513733 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 0.000105379922351636 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.134469584623973 Total time 0.208523817857107 Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE Asked to drop 0 genes and 574 cells Cotan analysis functions started Genes/cells selection done: dropped [0] genes and [0] cells Working on [600] genes and [626] cells Estimate dispersion: START Effective number of cores used: 1 Executing 1 genes batches from [1:600] to [1:600] Estimate dispersion: DONE dispersion | min: -0.03839111328125 | max: 17.40625 | % negative: 6.66666666666667 Only analysis time 0.0567740003267924 Cotan genes' coex estimation started Calculate genes' coex: START Retrieving expected genes' contingency table calculating NN.. done calculating NY..YN..YY..t().. done Calculating genes' coex normalization factor Fraction of genes with very low expected contingency tables: 5.54631170271769e-05 Retrieving observed genes' yes/yes contingency table calculating YY.. done Estimating genes' coex Calculate genes' coex: DONE Only genes' coex time 0.123574550946554 Total time 0.19504968325297 Calculate GDI dataframe: START Using S Calculating S: START Calculating S: DONE S matrix sorted Calculate GDI dataframe: DONE [ FAIL 0 | WARN 1 | SKIP 0 | PASS 401 ] [ FAIL 0 | WARN 1 | SKIP 0 | PASS 401 ] > > proc.time() user system elapsed 622.21 4.65 625.95
COTAN.Rcheck/COTAN-Ex.timings
name | user | system | elapsed | |
COTAN | 0.87 | 0.02 | 0.89 | |
COTANObjectCreation | 12.91 | 0.14 | 12.80 | |
CalculatingCOEX | 72.86 | 1.10 | 72.96 | |
ClustersList | 0.00 | 0.01 | 0.01 | |
GenesCoexSpace | 14.69 | 0.24 | 14.63 | |
HandleMetaData | 0.11 | 0.03 | 0.14 | |
HandlingClusterizations | 25.05 | 1.54 | 25.78 | |
HandlingConditions | 0.11 | 0.05 | 0.16 | |
HeatmapPlots | 62.55 | 1.66 | 63.41 | |
LegacyFastSymmMatrix | 0 | 0 | 0 | |
LoggingFunctions | 0 | 0 | 0 | |
ParametersEstimations | 38.11 | 0.73 | 38.80 | |
RawDataCleaning | 6.53 | 0.19 | 7.06 | |
RawDataGetters | 0.07 | 0.03 | 0.10 | |
UniformClusters | 172.99 | 1.02 | 173.13 | |
getColorsVector | 0 | 0 | 0 | |