__STDOUT LOG__
Job runs on fgcz-h-163
at /scratch/o5495_o5444_ScSeurat_2024-12-05--10-02-59_Differentiated_lung_cells_temp1431868
Starting EzAppScSeurat ScSeurat o5495_o5444_ScSeurat_2024-12-05--10-02-59_Differentiated_lung_cells_temp1431868 2024-12-05 10:03:11
Uploading data to Enrichr... Done.
Querying Azimuth_Cell_Types_2021... Done.
Parsing results... Done.
Uploading data to Enrichr... Done.
Querying Azimuth_Cell_Types_2021... Done.
Parsing results... Done.
Uploading data to Enrichr... Done.
Querying Azimuth_Cell_Types_2021... Done.
Parsing results... Done.
Uploading data to Enrichr... Done.
Querying Azimuth_Cell_Types_2021... Done.
Parsing results... Done.
Uploading data to Enrichr... Done.
Querying Azimuth_Cell_Types_2021... Done.
Parsing results... Done.
Uploading data to Enrichr... Done.
Querying Azimuth_Cell_Types_2021... Done.
Parsing results... Done.
Uploading data to Enrichr... Done.
Querying Azimuth_Cell_Types_2021... Done.
Parsing results... Done.
ezRun tag: 733d7a85c98ed8bb0732c178986b67ce4584e581
ezRun github link: https://github.com/uzh/ezRun/tree/733d7a85c98ed8bb0732c178986b67ce4584e581
R version 4.4.0 (2024-04-24)
Platform: x86_64-pc-linux-gnu
Running under: Debian GNU/Linux 12 (bookworm)
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
time zone: Europe/Zurich
tzcode source: system (glibc)
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] SoupX_1.6.2 celda_1.20.0
[3] scran_1.32.0 scater_1.32.0
[5] future_1.33.2 Azimuth_0.5.0
[7] shinyBS_0.62 decoupleR_2.10.0
[9] enrichR_3.2 DropletUtils_1.24.0
[11] scuttle_1.14.0 BiocParallel_1.38.0
[13] scDblFinder_1.18.0 SingleCellExperiment_1.26.0
[15] Seurat_5.1.0 SeuratObject_5.0.2
[17] sp_2.1-4 SingleR_2.6.0
[19] SummarizedExperiment_1.34.0 GSEABase_1.66.0
[21] graph_1.82.0 annotate_1.82.0
[23] XML_3.99-0.16.1 AnnotationDbi_1.66.0
[25] Biobase_2.64.0 AUCell_1.26.0
[27] HDF5Array_1.32.0 rhdf5_2.48.0
[29] DelayedArray_0.30.1 SparseArray_1.4.8
[31] S4Arrays_1.4.1 abind_1.4-5
[33] MatrixGenerics_1.16.0 matrixStats_1.3.0
[35] Matrix_1.7-0 ezRun_3.19.1
[37] lubridate_1.9.3 forcats_1.0.0
[39] stringr_1.5.1 dplyr_1.1.4
[41] purrr_1.0.2 readr_2.1.5
[43] tidyr_1.3.1 tibble_3.2.1
[45] ggplot2_3.5.1 tidyverse_2.0.0
[47] GenomicRanges_1.56.1 Biostrings_2.72.1
[49] GenomeInfoDb_1.40.1 XVector_0.44.0
[51] IRanges_2.38.0 S4Vectors_0.42.0
[53] BiocGenerics_0.50.0 data.table_1.15.4
loaded via a namespace (and not attached):
[1] R.methodsS3_1.8.2 poweRlaw_0.80.0
[3] goftest_1.2-3 DT_0.33
[5] vctrs_0.6.5 spatstat.random_3.2-3
[7] digest_0.6.35 png_0.1-8
[9] gypsum_1.0.1 ggrepel_0.9.5
[11] deldir_2.0-4 parallelly_1.37.1
[13] combinat_0.0-8 MASS_7.3-61
[15] Signac_1.13.0 reshape2_1.4.4
[17] foreach_1.5.2 httpuv_1.6.15
[19] withr_3.0.0 survival_3.7-0
[21] EnsDb.Hsapiens.v86_2.99.0 memoise_2.0.1
[23] ggbeeswarm_0.7.2 zoo_1.8-12
[25] gtools_3.9.5 pbapply_1.7-2
[27] R.oo_1.26.0 KEGGREST_1.44.0
[29] promises_1.3.0 httr_1.4.7
[31] restfulr_0.0.15 globals_0.16.3
[33] fitdistrplus_1.1-11 rhdf5filters_1.16.0
[35] UCSC.utils_1.0.0 miniUI_0.1.1.1
[37] generics_0.1.3 curl_5.2.1
[39] zlibbioc_1.50.0 ScaledMatrix_1.12.0
[41] polyclip_1.10-6 ExperimentHub_2.12.0
[43] GenomeInfoDbData_1.2.12 RcppEigen_0.3.4.0.0
[45] doParallel_1.0.17 xtable_1.8-4
[47] pracma_2.4.4 BiocFileCache_2.12.0
[49] hms_1.1.3 irlba_2.3.5.1
[51] filelock_1.0.3 colorspace_2.1-1
[53] hdf5r_1.3.10 ROCR_1.0-11
[55] reticulate_1.37.0 spatstat.data_3.0-4
[57] magrittr_2.0.3 lmtest_0.9-40
[59] glmGamPoi_1.16.0 later_1.3.2
[61] viridis_0.6.5 lattice_0.22-6
[63] spatstat.geom_3.2-9 future.apply_1.11.2
[65] scattermore_1.2 cowplot_1.1.3
[67] RcppAnnoy_0.0.22 pillar_1.9.0
[69] nlme_3.1-165 iterators_1.0.14
[71] pwalign_1.0.0 caTools_1.18.2
[73] compiler_4.4.0 beachmat_2.20.0
[75] RSpectra_0.16-1 stringi_1.8.4
[77] tensor_1.5 MCMCprecision_0.4.0
[79] GenomicAlignments_1.40.0 plyr_1.8.9
[81] crayon_1.5.2 BiocIO_1.14.0
[83] googledrive_2.1.1 locfit_1.5-9.9
[85] bit_4.0.5 fastmatch_1.1-4
[87] codetools_0.2-20 BiocSingular_1.20.0
[89] alabaster.ranges_1.4.1 SeuratData_0.2.2.9001
[91] plotly_4.10.4 mime_0.12
[93] splines_4.4.0 Rcpp_1.0.12
[95] fastDummies_1.7.3 dbplyr_2.5.0
[97] sparseMatrixStats_1.16.0 doMC_1.3.8
[99] cellranger_1.1.0 blob_1.2.4
[101] utf8_1.2.4 BiocVersion_3.19.1
[103] seqLogo_1.70.0 AnnotationFilter_1.28.0
[105] WriteXLS_6.6.0 fs_1.6.4
[107] listenv_0.9.1 DelayedMatrixStats_1.26.0
[109] statmod_1.5.0 tzdb_0.4.0
[111] pkgconfig_2.0.3 tools_4.4.0
[113] cachem_1.1.0 RSQLite_2.3.7
[115] viridisLite_0.4.2 DBI_1.2.3
[117] celldex_1.14.0 fastmap_1.2.0
[119] scales_1.3.0 grid_4.4.0
[121] ica_1.0-3 shinydashboard_0.7.2
[123] Rsamtools_2.20.0 AnnotationHub_3.12.0
[125] patchwork_1.2.0 BiocManager_1.30.23
[127] dotCall64_1.1-1 alabaster.schemas_1.4.0
[129] RANN_2.6.1 yaml_2.3.8
[131] rtracklayer_1.64.0 cli_3.6.2
[133] leiden_0.4.3.1 lifecycle_1.0.4
[135] uwot_0.2.2 presto_1.0.0
[137] bluster_1.14.0 BSgenome.Hsapiens.UCSC.hg38_1.4.5
[139] timechange_0.3.0 gtable_0.3.5
[141] rjson_0.2.21 ggridges_0.5.6
[143] progressr_0.14.0 parallel_4.4.0
[145] limma_3.60.2 jsonlite_1.8.8
[147] edgeR_4.2.0 RcppHNSW_0.6.0
[149] TFBSTools_1.42.0 bitops_1.0-7
[151] bit64_4.0.5 xgboost_1.7.7.1
[153] Rtsne_0.17 alabaster.matrix_1.4.0
[155] spatstat.utils_3.0-5 BiocNeighbors_1.22.0
[157] CNEr_1.40.0 alabaster.se_1.4.1
[159] metapod_1.12.0 dqrng_0.4.1
[161] shinyjs_2.1.0 SeuratDisk_0.0.0.9021
[163] R.utils_2.12.3 alabaster.base_1.4.1
[165] lazyeval_0.2.2 shiny_1.9.1
[167] htmltools_0.5.8.1 GO.db_3.19.1
[169] sctransform_0.4.1 rappdirs_0.3.3
[171] ensembldb_2.28.0 glue_1.7.0
[173] TFMPvalue_0.0.9 spam_2.10-0
[175] googlesheets4_1.1.1 httr2_1.0.1
[177] RCurl_1.98-1.14 BSgenome_1.72.0
[179] gridExtra_2.3 JASPAR2020_0.99.10
[181] igraph_2.0.3 R6_2.5.1
[183] RcppRoll_0.3.0 GenomicFeatures_1.56.0
[185] cluster_2.1.6 Rhdf5lib_1.26.0
[187] gargle_1.5.2 DirichletMultinomial_1.46.0
[189] tidyselect_1.2.1 vipor_0.4.7
[191] ProtGenerics_1.36.0 rsvd_1.0.5
[193] munsell_0.5.1 KernSmooth_2.23-24
[195] htmlwidgets_1.6.4 RColorBrewer_1.1-3
[197] rlang_1.1.4 spatstat.sparse_3.0-3
[199] spatstat.explore_3.2-7 fansi_1.0.6
[201] beeswarm_0.4.0
Finished EzAppScSeurat ScSeurat o5495_o5444_ScSeurat_2024-12-05--10-02-59_Differentiated_lung_cells_temp1431868 2024-12-05 10:41:17
__STDERR LOG__
Loading required package: data.table
Loading required package: Biostrings
Loading required package: BiocGenerics
Attaching package: ‘BiocGenerics’
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IQR, mad, sd, var, xtabs
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anyDuplicated, aperm, append, as.data.frame, basename, cbind,
colnames, dirname, do.call, duplicated, eval, evalq, Filter, Find,
get, grep, grepl, intersect, is.unsorted, lapply, Map, mapply,
match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
Position, rank, rbind, Reduce, rownames, sapply, setdiff, table,
tapply, union, unique, unsplit, which.max, which.min
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Loading required package: stats4
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Loading required package: GenomicRanges
Loading required package: tidyverse
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr 1.1.4 ✔ readr 2.1.5
✔ forcats 1.0.0 ✔ stringr 1.5.1
✔ ggplot2 3.5.1 ✔ tibble 3.2.1
✔ lubridate 1.9.3 ✔ tidyr 1.3.1
✔ purrr 1.0.2
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
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ℹ Use the conflicted package () to force all conflicts to become errors
unknown param: partition
unknown param: tissue
unknown param: Azimuth
unknown param: SingleR
unknown param: cellxgeneUrl
unknown param: cellxgeneLabel
unknown param: sushi_app
unknown param: isLastJob
Loading required package: DelayedArray
Loading required package: Matrix
Attaching package: ‘Matrix’
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count
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colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
colWeightedMeans, colWeightedMedians, colWeightedSds,
colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
rowWeightedSds, rowWeightedVars
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Loading required package: rhdf5
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Loading required package: Biobase
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Attaching package: ‘Biobase’
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Attaching package: ‘Seurat’
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Loading required package: SingleCellExperiment
Welcome to enrichR
Checking connection ...
Enrichr ... Connection is Live!
FlyEnrichr ... Connection is Live!
WormEnrichr ... Connection is Live!
YeastEnrichr ... Connection is Live!
FishEnrichr ... Connection is Live!
OxEnrichr ... Connection is Live!
Attaching package: ‘decoupleR’
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:=
Registered S3 method overwritten by 'SeuratDisk':
method from
as.sparse.H5Group Seurat
Attaching shinyBS
failed to open the port 11479, trying a new port...
Loading required package: future
Assuming the input to be a matrix of counts or expected counts.
Clustering cells...
8 clusters
Creating ~7824 artificial doublets...
Dimensional reduction
Evaluating kNN...
Training model...
iter=0, 702 cells excluded from training.
iter=1, 551 cells excluded from training.
iter=2, 495 cells excluded from training.
Threshold found:0.382
481 (4.9%) doublets called
Loading required package: scran
Warning: Cannot find a parent environment called Seurat
Warning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session
10:32:03 UMAP embedding parameters a = 0.9922 b = 1.112
10:32:03 Read 9298 rows and found 20 numeric columns
10:32:03 Using Annoy for neighbor search, n_neighbors = 30
10:32:03 Building Annoy index with metric = cosine, n_trees = 50
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
10:32:04 Writing NN index file to temp file /tmp/RtmpFH6c5a/file15d9635b4e6462
10:32:04 Searching Annoy index using 4 threads, search_k = 3000
10:32:05 Annoy recall = 100%
10:32:07 Commencing smooth kNN distance calibration using 4 threads with target n_neighbors = 30
10:32:10 Initializing from normalized Laplacian + noise (using RSpectra)
10:32:10 Commencing optimization for 500 epochs, with 378798 positive edges
Using method 'umap'
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[----|----|----|----|----|----|----|----|----|----|
**************************************************|
10:32:21 Optimization finished
Attaching package: 'celda'
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params
--------------------------------------------------
Starting DecontX
--------------------------------------------------
Thu Dec 5 10:32:26 2024 .. Analyzing all cells
Thu Dec 5 10:32:26 2024 .... Generating UMAP
Thu Dec 5 10:33:01 2024 .... Estimating contamination
Thu Dec 5 10:33:05 2024 ...... Completed iteration: 10 | converge: 0.03674
Thu Dec 5 10:33:08 2024 ...... Completed iteration: 20 | converge: 0.01359
Thu Dec 5 10:33:11 2024 ...... Completed iteration: 30 | converge: 0.007252
Thu Dec 5 10:33:14 2024 ...... Completed iteration: 40 | converge: 0.004852
Thu Dec 5 10:33:17 2024 ...... Completed iteration: 50 | converge: 0.003361
Thu Dec 5 10:33:21 2024 ...... Completed iteration: 60 | converge: 0.002508
Thu Dec 5 10:33:24 2024 ...... Completed iteration: 70 | converge: 0.001944
Thu Dec 5 10:33:27 2024 ...... Completed iteration: 80 | converge: 0.00169
Thu Dec 5 10:33:30 2024 ...... Completed iteration: 90 | converge: 0.001221
Thu Dec 5 10:33:33 2024 ...... Completed iteration: 99 | converge: 0.0009892
Thu Dec 5 10:33:33 2024 .. Calculating final decontaminated matrix
--------------------------------------------------
Completed DecontX. Total time: 1.178252 mins
--------------------------------------------------
10 genes passed tf-idf cut-off and 0 soup quantile filter. Taking the top 0.
Error in autoEstCont(sc, tfidfMin = tfidfMin, forceAccept = T, doPlot = FALSE) :
No plausible marker genes found. Is the channel low complexity (see help)? If not, reduce tfidfMin or soupQuantile
230 genes passed tf-idf cut-off and 18 soup quantile filter. Taking the top 18.
Using 54 independent estimates of rho.
Estimated global rho of 0.03
Expanding counts from 7 clusters to 9298 cells.
Calculating cluster 0
Calculating cluster 1
Calculating cluster 2
Calculating cluster 3
Calculating cluster 4
Calculating cluster 5
Calculating cluster 6
Warning in .AUCell_calcAUC(geneSets = geneSets, rankings = rankings, nCores = nCores, :
The following gene sets will be excluded from the analysis(less than 20% of their genes are available):
Alveolar pneumocyte Type II, Anti-tumor immune cell, Conventional dendritic cell 1(cDC1), Conventional dendritic cell 2(cDC2), Effector T(Teff) cell, Exhausted CD8+ T cell
Error in H5Fopen(fpath) : HDF5. File accessibility. Unable to open file.
Calls: ... FUN -> readObject -> meth -> -> H5Fopen
In addition: Warning message:
In sparseMatrix(i = out@i[w] + 1, j = out@j[w] + 1, x = out@x[w], :
'giveCsparse' is deprecated; setting repr="T" for you
error exists: manon.bouzereau@uzh.ch
mail sent to: manon.bouzereau@uzh.ch
Execution halted