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###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:COTAN.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings COTAN_2.2.3.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.18-bioc-mac-arm64/meat/COTAN.Rcheck’
* using R version 4.3.2 (2023-10-31)
* using platform: aarch64-apple-darwin20 (64-bit)
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘COTAN/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘COTAN’ version ‘2.2.3’
* 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 ‘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 R 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’
cellsUniformClustering: no visible binding for global variable
  ‘objSeurat’
cellsUniformClustering: no visible binding for global variable
  ‘usedMaxResolution’
cellsUniformClustering: no visible binding for global variable
  ‘outputCoexDF’
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’
clustersTreePlot: no visible binding for global variable ‘clusters’
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’
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’
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 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 outputCoexDF rankGenes rawNorm secondaryMarkers
  sum.raw.norm usedMaxResolution values violinwidth width x xmax xmaxv
  xminv y zoomedNuPlot
* 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         202.465  1.654 204.745
HeatmapPlots             56.614  1.722  59.217
CalculatingCOEX          56.954  1.232  58.604
ParametersEstimations    27.381  0.928  28.356
HandlingClusterizations  26.349  0.429  27.113
GenesCoexSpace           15.769  0.244  16.087
COTANObjectCreation      14.517  0.190  14.714
RawDataCleaning           8.828  0.206   9.048
* 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 in ‘inst/doc’ ... 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
  ‘/Users/biocbuild/bbs-3.18-bioc-mac-arm64/meat/COTAN.Rcheck/00check.log’
for details.

##############################################################################
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###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL COTAN
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/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)

R version 4.3.2 (2023-10-31) -- "Eye Holes"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20 (64-bit)

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 <- 1.5
+   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)
+   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))
+ 
+   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 
  0.257   0.069   0.328 

R version 4.3.2 (2023-10-31) -- "Eye Holes"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20 (64-bit)

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 
  0.233   0.057   0.279 

R version 4.3.2 (2023-10-31) -- "Eye Holes"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20 (64-bit)

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.. 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 5 genes batches from [1:2] 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 7 cells batches from [1:3] 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: 0.836359531101204 | median 0.703684202571891 | mean: 0.645537958989613
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: 0.259872988828244 | 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: 0.0951586919577014 | median 0.0794297037094678 | 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: 0.0327747321002274 | median 0.0272104747849538 | mean: 0.0248963830312045
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 0.00942326497706159 | mean: 0.00863113610779553
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: 0.00387133150664809 | median 0.00310910176088619 | 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: 0.000943992659051496
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: 0.000364602956585358 | median 0.000313956936820681 | mean: 0.00028289957431813
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.. 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.. 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: 0.803213159865939 | median 0.677497553540581 | mean: 0.61937543089282
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 0.206232152124437 | 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: 0.0916983669060105 | median 0.0765266929824957 | mean: 0.0697593208689694
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: 0.0317151207459219 | median 0.0262702142278242 | mean: 0.0240886952086946
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: 0.011369331635624 | median 0.00939669372836338 | 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 0.00343393462175712 | mean: 0.00313496757119474
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: 0.00143433714371355 | median 0.00116636244706836 | mean: 0.00109289166947821
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: 0.000379524846206181 | median 0.000325685250688323 | mean: 0.000295532844331703
Estimate dispersion/nu: DONE
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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.. 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
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.. 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.. done
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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
calculating YY.. done
calculating YY.. done
calculating NY..YN..NN.. 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 5 cells batches from [1:4] 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: 0.255353289373156 | median 0.0807577993228152 | mean: 0.101980750205761
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 5 cells batches from [1:4] 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: 0.00326864580272179 | median 0.00111524657842743 | mean: 0.00131556083122621
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 5 cells batches from [1:4] to [17:20]
Estimate nu: DONE
nu change (abs) | max: 0 | median:  0 | mean:  0
Nu mean: 1.69735147626627
Marginal errors | max: 7.56328383619831e-05 | median 1.7294808722923e-05 | mean: 2.99252342140122e-05
Estimate dispersion/nu: DONE
calculating NN.. done
calculating NN.. done
calculating YN..NY..YY.. done
Calculate cells' coex: START
Retrieving expected cells' contingency table
calculating NN.. done
calculating YN..NY..YY.. 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
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 5 cells batches from [1:4] 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: 0.255353289373156 | median 0.0807577993228152 | mean: 0.101980750205761
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 5 cells batches from [1:4] 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: 0.00326864580272179 | median 0.00111524657842743 | mean: 0.00131556083122621
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 5 cells batches from [1:4] to [17:20]
Estimate nu: DONE
nu change (abs) | max: 0 | median:  0 | mean:  0
Nu mean: 1.69735147626627
Marginal errors | max: 7.56328383619831e-05 | median 1.7294808722923e-05 | mean: 2.99252342140122e-05
Estimate dispersion/nu: DONE
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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.. done
calculating NN.. done
calculating NY..YN..YY.. 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.. done
calculating NN.. done
calculating NY..YN..YY.. 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
Using S
Calculating S: START
Calculating S: DONE
Calculate GDI dataframe: START
Calculate GDI dataframe: DONE
Using G
Calculating G: START
calculating YY.. done
calculating YN..NY..NN.. done
calculating NN.. done
calculating NY..YN..YY.. done
Estimating G
Calculating G: DONE
Calculate GDI dataframe: START
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
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 0.056011950969696
Cotan genes' coex estimation started
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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 0.163595247268677
Total time 0.234828682740529
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 0.0586621840794881
Cotan genes' coex estimation started
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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 0.163106183211009
Total time 0.237565048535665
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
Using S
Calculating S: START
Calculating S: DONE
Calculate GDI dataframe: START
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 0.153988333543142
Saving elaborated data locally at: /tmp/RtmpGurpds/test.cotan.RDS
Creating cells' uniform clustering: START
In iteration 0 the number of cells to re-cluster is 1200 cells belonging to 0 clusters
Creating Seurat object: START
Performing log-normalization
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
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-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 
Negative:  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 
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
10:27:11 UMAP embedding parameters a = 0.9922 b = 1.112
Found more than one class "dist" in cache; using the first, from namespace 'BiocGenerics'
Also defined by 'spam'
10:27:11 Read 1200 rows and found 50 numeric columns
10:27:11 Using Annoy for neighbor search, n_neighbors = 30
Found more than one class "dist" in cache; using the first, from namespace 'BiocGenerics'
Also defined by 'spam'
10:27:11 Building Annoy index with metric = cosine, n_trees = 50
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
10:27:11 Writing NN index file to temp file /tmp/RtmpGurpds/file5eae2c46b839
10:27:11 Searching Annoy index using 1 thread, search_k = 3000
10:27:11 Annoy recall = 100%
10:27:12 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30
10:27:14 Initializing from normalized Laplacian + noise (using RSpectra)
10:27:14 Commencing optimization for 500 epochs, with 42274 positive edges
Using method 'umap'
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
10:27:18 Optimization finished
Creating PDF UMAP in file:/tmp/RtmpGurpds/test/reclustering_0/pdf_umap.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 0.0490430315335592
Cotan genes' coex estimation started
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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 0.145553568998973
Total time 0.209716482957204
Checking uniformity for the cluster '0' with 353 cells
Using S
Calculating S: START
Calculating S: DONE
Calculate GDI dataframe: START
Calculate GDI dataframe: DONE
GDI plot
Removed 0 low GDI genes (such as the fully-expressed) in GDI plot
Cluster 0 is uniform
0.17% of the genes is above the given GDI threshold 1.5
GDI 99% quantile is at 1.4439
cluster 0 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 0.0509429017702738
Cotan genes' coex estimation started
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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 0.148769581317902
Total time 0.215207513173421
Checking uniformity for the cluster '1' with 321 cells
Using S
Calculating S: START
Calculating S: DONE
Calculate GDI dataframe: START
Calculate GDI dataframe: DONE
GDI plot
Removed 0 low GDI genes (such as the fully-expressed) in GDI plot
Cluster 1 is uniform
0.17% of the genes is above the given GDI threshold 1.5
GDI 99% quantile is at 1.4305
cluster 1 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 0.0500363866488139
Cotan genes' coex estimation started
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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 0.150617730617523
Total time 0.216603914896647
Checking uniformity for the cluster '2' with 295 cells
Using S
Calculating S: START
Calculating S: DONE
Calculate GDI dataframe: START
Calculate GDI dataframe: DONE
GDI plot
Removed 0 low GDI genes (such as the fully-expressed) in GDI plot
Cluster 2 is uniform
0% of the genes is above the given GDI threshold 1.5
GDI 99% quantile is at 1.3925
cluster 2 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 0.0498451670010885
Cotan genes' coex estimation started
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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 0.147907932599386
Total time 0.214270714918772
Checking uniformity for the cluster '3' with 231 cells
Using S
Calculating S: START
Calculating S: DONE
Calculate GDI dataframe: START
Calculate GDI dataframe: DONE
GDI plot
Removed 0 low GDI genes (such as the fully-expressed) in GDI plot
Cluster 3 is uniform
0% of the genes is above the given GDI threshold 1.5
GDI 99% quantile is at 1.373
cluster 3 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: 00_0000, 00_0001, 00_0002, 00_0003
Differential Expression Analysis - START
* analysis of cluster: '1' - START
* analysis of cluster: '1' - DONE
* analysis of cluster: '2' - START
* analysis of cluster: '2' - DONE
* analysis of cluster: '3' - START
* analysis of cluster: '3' - DONE
* analysis of cluster: '4' - START
* analysis of cluster: '4' - DONE

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
10:28:42 UMAP embedding parameters a = 0.9922 b = 1.112
Found more than one class "dist" in cache; using the first, from namespace 'BiocGenerics'
Also defined by 'spam'
10:28:42 Read 1200 rows and found 25 numeric columns
10:28:42 Using Annoy for neighbor search, n_neighbors = 30
Found more than one class "dist" in cache; using the first, from namespace 'BiocGenerics'
Also defined by 'spam'
10:28:42 Building Annoy index with metric = cosine, n_trees = 50
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
10:28:42 Writing NN index file to temp file /tmp/RtmpGurpds/file5eae163efcda
10:28:42 Searching Annoy index using 1 thread, search_k = 3000
10:28:43 Annoy recall = 100%
10:28:44 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30
10:28:46 Initializing from normalized Laplacian + noise (using RSpectra)
10:28:46 Commencing optimization for 500 epochs, with 43428 positive edges
Using method 'umap'
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
10:28:50 Optimization finished
Creating cells' uniform clustering: DONE
Differential Expression Analysis - START
* analysis of cluster: '1' - START
* analysis of cluster: '1' - DONE
* analysis of cluster: '2' - START
* analysis of cluster: '2' - DONE
* analysis of cluster: '3' - START
* analysis of cluster: '3' - DONE
* analysis of cluster: '4' - START
* analysis of cluster: '4' - DONE

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 0.0500221490859985
Cotan genes' coex estimation started
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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 0.147994617621104
Total time 0.21296671628952
Checking uniformity for the cluster 'Cluster_2' with 295 cells
Using S
Calculating S: START
Calculating S: DONE
Calculate GDI dataframe: START
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 1.5
GDI 99% quantile is at 1.3925
findClustersMarkers - START
Differential Expression Analysis - START
* analysis of cluster: '1' - START
* analysis of cluster: '1' - DONE
* analysis of cluster: '2' - START
* analysis of cluster: '2' - DONE
* analysis of cluster: '3' - START
* analysis of cluster: '3' - DONE
* analysis of cluster: '4' - START
* analysis of cluster: '4' - DONE

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
findClustersMarkers - DONE
findClustersMarkers - START
Differential Expression Analysis - START
* analysis of cluster: '1' - START
* analysis of cluster: '1' - DONE
* analysis of cluster: '2' - START
* analysis of cluster: '2' - DONE
* analysis of cluster: '3' - START
* analysis of cluster: '3' - DONE
* analysis of cluster: '4' - START
* analysis of cluster: '4' - DONE

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
findClustersMarkers - DONE
findClustersMarkers - START
Differential Expression Analysis - START
* analysis of cluster: '1' - START
* analysis of cluster: '1' - DONE
* analysis of cluster: '2' - START
* analysis of cluster: '2' - DONE
* analysis of cluster: '3' - START
* analysis of cluster: '3' - DONE
* analysis of cluster: '4' - START
* analysis of cluster: '4' - DONE

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
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 0.0495096166928609
Cotan genes' coex estimation started
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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 0.146673119068146
Total time 0.211159765720367
Using S
Calculating S: START
Calculating S: DONE
Calculate GDI dataframe: START
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 0.0507084846496582
Cotan genes' coex estimation started
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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 0.147158316771189
Total time 0.213179516792297
Using S
Calculating S: START
Calculating S: DONE
Calculate GDI dataframe: START
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 0.0634111682573954
Cotan genes' coex estimation started
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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 0.169567183653514
Total time 0.24895175298055
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
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
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 0.0920716842015584
Differential Expression Analysis - START
* analysis of cluster: '1' - START
* analysis of cluster: '1' - DONE
* analysis of cluster: '2' - START
* analysis of cluster: '2' - DONE
* analysis of cluster: '3' - START
* analysis of cluster: '3' - DONE
* analysis of cluster: '4' - START
* analysis of cluster: '4' - DONE

Differential Expression 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 1.22034802329656
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
* analysis of cluster: '1' - START
* analysis of cluster: '1' - DONE
* analysis of cluster: '2' - START
* analysis of cluster: '2' - DONE
* analysis of cluster: '3' - START
* analysis of cluster: '3' - DONE
* analysis of cluster: '4' - START
* analysis of cluster: '4' - DONE

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 0.0523664156595866
Cotan genes' coex estimation started
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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 0.15433163245519
Total time 0.222794198989868
Checking uniformity for the cluster '1_2-merge' with 574 cells
Using S
Calculating S: START
Calculating S: DONE
Calculate GDI dataframe: START
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
0.33% of the genes is above the given GDI threshold 1.5
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 0.0529881159464518
Cotan genes' coex estimation started
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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 0.156234832604726
Total time 0.224772266546885
Checking uniformity for the cluster '3_4-merge' with 626 cells
Using S
Calculating S: START
Calculating S: DONE
Calculate GDI dataframe: START
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
0.83% of the genes is above the given GDI threshold 1.5
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
* analysis of cluster: '1_2-merge' - START
* analysis of cluster: '1_2-merge' - DONE
* analysis of cluster: '3_4-merge' - START
* analysis of cluster: '3_4-merge' - DONE

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 0.059658682346344
Cotan genes' coex estimation started
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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 0.1712744196256
Total time 0.247187085946401
Checking uniformity for the cluster '1_2-merge_3_4-merge-merge' with 1200 cells
Using S
Calculating S: START
Calculating S: DONE
Calculate GDI dataframe: START
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
15% of the genes is above the given GDI threshold 1.5
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
Applied reordering to clusterization is:
1  ->  1, 2  ->  2
Merging cells' uniform clustering: DONE
Applied reordering to clusterization is:
1  ->  1, 2  ->  2
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 0.0517201860745748
Cotan genes' coex estimation started
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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 0.154668883482615
Total time 0.22255718310674
Using S
Calculating S: START
Calculating S: DONE
Calculate GDI dataframe: START
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 0.0522703488667806
Cotan genes' coex estimation started
Calculate genes' coex: START
Retrieving expected genes' contingency table
calculating NN.. done
calculating NY..YN..YY.. 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 0.153895835081736
Total time 0.22294016679128
Using S
Calculating S: START
Calculating S: DONE
Calculate GDI dataframe: START
Calculate GDI dataframe: DONE
[ FAIL 0 | WARN 0 | SKIP 0 | PASS 359 ]
> 
> proc.time()
   user  system elapsed 
645.358   4.531 651.381