Back to Books build report for BioC 3.13

BUILD report for OSCA on malbec2

This page was generated on 2021-01-15 16:45:06 -0500 (Fri, 15 Jan 2021).

TO THE DEVELOPERS/MAINTAINERS OF THE OSCA PACKAGE: Please make sure to use the following settings in order to reproduce any error or warning you see on this page.
Package 2/3HostnameOS / ArchINSTALLBUILD
OSCA 1.1.13
Aaron Lun
Snapshot Date: 2021-01-15 09:00:02 -0500 (Fri, 15 Jan 2021)
URL: https://git.bioconductor.org/packages/OSCA
Branch: master
Last Commit: a99ce06
Last Changed Date: 2021-01-04 03:38:38 -0500 (Mon, 04 Jan 2021)
malbec2 Linux (Ubuntu 20.04.1 LTS) / x86_64  OK [ ERROR ]
riesling1 Windows Server 2019 Standard / x64  OK  ERROR 

Summary

Package: OSCA
Version: 1.1.13
Command: /home/biocbuild/bbs-3.13-bioc/R/bin/R CMD build --keep-empty-dirs --no-resave-data OSCA
StartedAt: 2021-01-15 10:30:40 -0500 (Fri, 15 Jan 2021)
EndedAt: 2021-01-15 14:19:45 -0500 (Fri, 15 Jan 2021)
EllapsedTime: 13745.6 seconds
RetCode: 1
Status:  ERROR 
PackageFile: None
PackageFileSize: NA

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.13-bioc/R/bin/R CMD build --keep-empty-dirs --no-resave-data OSCA
###
##############################################################################
##############################################################################


* checking for file ‘OSCA/DESCRIPTION’ ... OK
* preparing ‘OSCA’:
* checking DESCRIPTION meta-information ... OK
* installing the package to build vignettes
* creating vignettes ... ERROR
--- re-building ‘stub.Rmd’ using rmarkdown
--- finished re-building ‘stub.Rmd’

cd book && "/home/biocbuild/bbs-3.13-bioc/R/bin/R" -e "bookdown::render_book('index.Rmd')"

R Under development (unstable) (2021-01-05 r79797) -- "Unsuffered Consequences"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (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.

  Natural language support but running in an English locale

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.

> bookdown::render_book('index.Rmd')


processing file: index.Rmd

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output file: index.knit.md



processing file: installation.Rmd

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output file: installation.knit.md



processing file: learning-r.Rmd

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output file: learning-r.knit.md



processing file: getting-datasets.Rmd

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Loading required package: dbplyr
adding rname 'ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE85nnn/GSE85241/suppl/GSE85241%5Fcellsystems%5Fdataset%5F4donors%5Fupdated%2Ecsv%2Egz'

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Loading required package: SingleCellExperiment
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Attaching package: 'MatrixGenerics'

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    colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
    colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
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    colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
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    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,
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Loading required package: GenomicRanges
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    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
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Loading required package: IRanges
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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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adding rname 'ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE61nnn/GSE61533/suppl/GSE61533_HTSEQ_count_results.xls.gz'
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output file: getting-datasets.knit.md



processing file: sce-class.Rmd

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    colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
    colWeightedMeans, colWeightedMedians, colWeightedSds,
    colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
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    rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
    rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
    rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
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    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
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Loading required package: IRanges
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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")'.


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Welcome to Bioconductor

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---------------------
Welcome to dendextend version 1.14.0
Type citation('dendextend') for how to cite the package.

Type browseVignettes(package = 'dendextend') for the package vignette.
The github page is: https://github.com/talgalili/dendextend/

Suggestions and bug-reports can be submitted at: https://github.com/talgalili/dendextend/issues
Or contact: <tal.galili@gmail.com>

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	endothelial-mural: 	7 (8% of 83)
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	Zheng_Cord_Blood_C1_Putative_Megakaryocyte_Progenitor: 	10 (10% of 98)
	Zheng_Cord_Blood_C2_Putative_Basophil_Eosinophil_Mast_cell_Progenitor: 	4 (4% of 96)
	Zheng_Cord_Blood_C3_Megakaryocyte_Erythroid_Progenitor: 	5 (5% of 100)
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	Zheng_Cord_Blood_C8_Putative_Lymphoid_Primed_Multipotent_Progenitor_2: 	20 (21% of 97)
	Zheng_Cord_Blood_C9_Granulocyte_Macrophage_Progenitor: 	6 (6% of 100)
	Zheng_Cord_Blood_C10_Multilymphoid_Progenitor: 	13 (13% of 97)
	Gao_Esophagus_25W_C1_Ciliated_Epithelial_Cells: 	64 (14% of 455)
	Gao_Esophagus_25W_C2_KRT6Bpos_Secretory_Progenitor_Cells: 	10 (13% of 77)
	Gao_Esophagus_25W_C3_FGFR1Low_Epithelial_Cells: 	6 (12% of 52)
	Gao_Esophagus_25W_C4_FGFR1High_Epithelial_Cells: 	23 (11% of 208)
	Gao_Stomach_24W_C1_PROCRpos_Multipotent_Progenitor: 	1 (2% of 40)
	Gao_Stomach_24W_C2_TFF2pos_Multipotent_Progenitor: 	1 (14% of 7)
	Gao_Stomach_24W_C5_Putative_Pit_Cell_Progenitor: 	5 (9% of 55)
	Gao_Small_Intestine_24W_C2_PROCRpos_Progenitor: 	1 (5% of 22)
	Gao_Small_Intestine_24W_C3_Enterocyte_Progenitor_Subtype_1: 	2 (4% of 48)
	Gao_Small_Intestine_24W_C4_Enterocyte_Progenitor_Subtype_2: 	13 (14% of 96)
	Gao_Small_Intestine_24W_C6_Goblet_Cells: 	3 (7% of 44)
	Gao_Small_Intestine_24W_C7_Secretory_Progenitor: 	10 (20% of 51)
	Gao_Small_Intestine_24W_C9_Enteroendocrine_Cell: 	17 (28% of 60)
	Gao_Large_Intestine_24W_C1_DCLK1pos_Progenitor: 	4 (4% of 99)
	Gao_Large_Intestine_24W_C2_MKI67pos_Progenitor: 	6 (5% of 113)
	Gao_Large_Intestine_24W_C5_LGR5pos_Stem_Cell: 	6 (10% of 60)
	Gao_Large_Intestine_24W_C6_Secretory_Progenitor: 	3 (14% of 21)
	Gao_Large_Intestine_24W_C8_Goblet_Cell: 	1 (2% of 41)
	Gao_Large_Intestine_24W_C10_Enterocyte: 	7 (12% of 56)
	Gao_Large_Intestine_24W_C11_Paneth_Like_Cell: 	20 (6% of 323)
	Gao_Large_Intestine_Adult_CA_enteroendocrine_cells: 	28 (9% of 309)
	Gao_Large_Intestine_Adult_CE_OLFM4high_Stem_Cell: 	45 (12% of 362)
	Gao_Large_Intestine_Adult_CF_Goblet_Cell_Subtype_1: 	2 (9% of 23)
	Gao_Large_Intestine_Adult_CG_Goblet_Cell_Subtype_2: 	11 (20% of 55)
	Gao_Large_Intestine_Adult_CH_MKI67high_Cells: 	9 (8% of 107)
	Gao_Large_Intestine_Adult_CI_Mesenchymal_Cells: 	44 (12% of 361)
	Gao_Large_Intestine_Adult_CJ_Immune_Cells: 	40 (8% of 503)
	Zhong_PFC_Major_Types_Astrocytes: 	26 (8% of 325)
	Zhong_PFC_Major_Types_Excitatory_Neuron: 	1 (12% of 8)
	Zhong_PFC_Major_Types_Microglia: 	31 (7% of 437)
	Zhong_PFC_Major_Types_NPCs: 	9 (6% of 142)
	Zhong_PFC_Major_Types_OPC: 	7 (8% of 91)
	Zhong_PFC_C7_oRG_undergoing_Neuronal_Differentiation: 	9 (13% of 67)
	Zhong_PFC_C8_oRG_Proliferating: 	2 (3% of 62)
	Zhong_PFC_C9_oRG_Other: 	8 (10% of 83)
	Zhong_PFC_C3_Unknown_INP: 	4 (11% of 38)
	Zhong_PFC_C4_Unknown_INP: 	6 (7% of 89)
	Zhong_PFC_C5_BCL11B_CALB2_pos_INP: 	1 (5% of 22)
	Zhong_PFC_HES1_pos_C1_NPC: 	1 (17% of 6)
	Zhong_PFC_C2_Unknown_NPC: 	2 (3% of 75)
	Zhong_PFC_C1_NEUROD1_pos_Excitatory_Neuron: 	1 (4% of 26)
	Zhong_PFC_C2_SOX5_BCL11B_pos_Excitatory_Neuron: 	2 (7% of 28)
	Zhong_PFC_C6_PLXNA4_pos_Excitatory_Neuron: 	1 (14% of 7)
	Zhong_PFC_C6_DLX5_GAD1_GAD2_pos_Interneuron: 	2 (13% of 15)
	Zhong_PFC_C7_SST_LHX6_pos_Putative_Migrating_Interneuron: 	2 (14% of 14)
	Zhong_PFC_C8_Unknown_NEUROD2_pos_Interneuron: 	5 (6% of 84)
	Zhong_PFC_C1_OPC: 	17 (7% of 237)
	Zhong_PFC_C2_THY1_pos_OPC: 	1 (4% of 27)
	Zhong_PFC_C3_HOPX_pos_OPC: 	1 (12% of 8)
	Zhong_PFC_C4_PTGDS_pos_OPC: 	9 (6% of 147)
	Zhong_PFC_C1_Astrocyte: 	4 (13% of 30)
	Zhong_PFC_C2_ASCL1_pos_Astrocyte: 	2 (33% of 6)
	Zhong_PFC_C3_Astrocyte: 	36 (9% of 386)
	Zhong_PFC_C1_Microglia: 	12 (5% of 255)
	Zhong_PFC_C3_Microglia: 	36 (7% of 488)
	Fan_Embryonic_CTX_Big_Groups_Cajal_Retzius: 	47 (9% of 499)
	Fan_Embryonic_CTX_Big_Groups_Brain_Endothelial: 	21 (6% of 365)
	Fan_Embryonic_CTX_Big_Groups_Excitatory_Neuron: 	6 (13% of 47)
	Fan_Embryonic_CTX_Big_Groups_Glial: 	6 (5% of 133)
	Fan_Embryonic_CTX_Big_Groups_Brain_Immune: 	12 (8% of 148)
	Fan_Embryonic_CTX_Big_Groups_Microglia: 	23 (6% of 371)
	Fan_Embryonic_CTX_EX_1_Excitatory_Neuron: 	2 (29% of 7)
	Fan_Embryonic_CTX_EX_2_Excitatory_Neuron: 	2 (12% of 16)
	Fan_Embryonic_CTX_EX_4_Excitatory_Neuron: 	17 (10% of 162)
	Fan_Embryonic_CTX_IN_1_Interneuron: 	1 (9% of 11)
	Fan_Embryonic_CTX_IN_2_Interneuron: 	2 (29% of 7)
	Fan_Embryonic_CTX_Astrocyte_1: 	8 (10% of 79)
	Fan_Embryonic_CTX_Astrocyte_2: 	20 (13% of 153)
	Fan_Embryonic_CTX_NSC_1: 	1 (6% of 18)
	Fan_Embryonic_CTX_NSC_2: 	11 (5% of 233)
	Fan_Embryonic_CTX_Olig: 	53 (7% of 753)
	Fan_Embryonic_CTX_OPC: 	7 (13% of 55)
	Fan_Embryonic_CTX_Brain_Endothelial_1: 	30 (7% of 439)
	Fan_Embryonic_CTX_Brain_Endothelial_2: 	18 (6% of 303)
	Fan_Embryonic_CTX_Microglia_1: 	8 (5% of 154)
	Fan_Embryonic_CTX_Microglia_3: 	2 (10% of 20)
	Fan_Embryonic_CTX_Brain_Myeloid: 	12 (9% of 139)
	Fan_Embryonic_CTX_Brain_B_cell: 	14 (14% of 100)
	Fan_Embryonic_CTX_Brain_Effector_T_cell: 	19 (15% of 131)
	Fan_Embryonic_CTX_Brain_Naive_like_T_cell: 	18 (11% of 158)
	Manno_Midbrain_Neurotypes_Basal: 	12 (15% of 79)
	Manno_Midbrain_Neurotypes_hEndo: 	63 (7% of 889)
	Manno_Midbrain_Neurotypes_hPeric: 	66 (8% of 795)
	Manno_Midbrain_Neurotypes_hMgl: 	31 (5% of 576)
	Manno_Midbrain_Neurotypes_hOPC: 	36 (10% of 365)
	Manno_Midbrain_Neurotypes_hRgl2c: 	35 (11% of 326)
	Manno_Midbrain_Neurotypes_hRgl2b: 	55 (13% of 439)
	Manno_Midbrain_Neurotypes_hRgl2a: 	63 (11% of 598)
	Manno_Midbrain_Neurotypes_hRgl3: 	62 (11% of 572)
	Manno_Midbrain_Neurotypes_hRgl1: 	39 (11% of 364)
	Manno_Midbrain_Neurotypes_hProgM: 	29 (9% of 306)
	Manno_Midbrain_Neurotypes_hProgBP: 	34 (11% of 300)
	Manno_Midbrain_Neurotypes_hProgFPL: 	31 (10% of 323)
	Manno_Midbrain_Neurotypes_hProgFPM: 	35 (10% of 355)
	Manno_Midbrain_Neurotypes_hNProg: 	21 (9% of 229)
	Manno_Midbrain_Neurotypes_hNbM: 	19 (6% of 295)
	Manno_Midbrain_Neurotypes_hNbML1: 	24 (7% of 327)
	Manno_Midbrain_Neurotypes_hRN: 	19 (6% of 333)
	Manno_Midbrain_Neurotypes_hNbML5: 	35 (8% of 465)
	Manno_Midbrain_Neurotypes_hDA: 	46 (9% of 507)
	Manno_Midbrain_Neurotypes_hDA1: 	34 (6% of 585)
	Manno_Midbrain_Neurotypes_hDA2: 	37 (7% of 514)
	Manno_Midbrain_Neurotypes_hNbGaba: 	58 (8% of 702)
	Manno_Midbrain_Neurotypes_hGaba: 	93 (8% of 1106)
	Manno_Midbrain_Neurotypes_hSert: 	41 (9% of 451)
	Manno_Midbrain_Neurotypes_hOMTN: 	26 (7% of 387)
	Hay_Bone_Marrow_CD34_pos_CLP: 	27 (32% of 85)
	Hay_Bone_Marrow_CD34_pos_Eo_B_Mast: 	23 (32% of 73)
	Hay_Bone_Marrow_CD34_pos_ERP: 	23 (33% of 69)
	Hay_Bone_Marrow_CD34_pos_ERP_Early: 	18 (25% of 73)
	Hay_Bone_Marrow_CD34_pos_Gran: 	44 (32% of 138)
	Hay_Bone_Marrow_CD34_pos_HSC: 	162 (27% of 607)
	Hay_Bone_Marrow_CD34_pos_HSC_cycle: 	17 (37% of 46)
	Hay_Bone_Marrow_CD34_pos_LMPP: 	46 (40% of 115)
	Hay_Bone_Marrow_CD34_pos_Lymphoid_UNK: 	18 (35% of 51)
	Hay_Bone_Marrow_CD34_pos_MDP_1: 	20 (53% of 38)
	Hay_Bone_Marrow_CD34_pos_MDP_2: 	11 (35% of 31)
	Hay_Bone_Marrow_CD34_pos_MEP: 	20 (43% of 46)
	Hay_Bone_Marrow_CD34_pos_MKP: 	39 (20% of 193)
	Hay_Bone_Marrow_CD34_pos_MultiLin: 	47 (27% of 174)
	Hay_Bone_Marrow_CD34_pos_pre_B: 	134 (26% of 519)
	Hay_Bone_Marrow_CD34_pos_pre_B_cycling: 	44 (44% of 99)
	Hay_Bone_Marrow_CD34_pos_pre_PC: 	190 (28% of 679)
	Hay_Bone_Marrow_CD34_pos_pre_T: 	15 (47% of 32)
	Hay_Bone_Marrow_CD8_T_cell: 	155 (28% of 551)
	Hay_Bone_Marrow_Dendritic_Cell: 	175 (24% of 721)
	Hay_Bone_Marrow_Early_Erythroblast: 	76 (12% of 648)
	Hay_Bone_Marrow_Eosinophil: 	109 (24% of 456)
	Hay_Bone_Marrow_Follicular_B_cell: 	223 (31% of 710)
	Hay_Bone_Marrow_Granulocytic_UNK: 	28 (32% of 87)
	Hay_Bone_Marrow_Immature_Neutrophil: 	159 (18% of 876)
	Hay_Bone_Marrow_Monocyte: 	164 (24% of 686)
	Hay_Bone_Marrow_Naive_T_cell: 	386 (25% of 1561)
	Hay_Bone_Marrow_Neutrophil: 	233 (17% of 1356)
	Hay_Bone_Marrow_NK_cells: 	246 (13% of 1842)
	Hay_Bone_Marrow_Plasma_Cell: 	247 (49% of 509)
	Hay_Bone_Marrow_Platelet: 	104 (22% of 481)
	Hay_Bone_Marrow_Pre_Dendritic: 	31 (38% of 82)
	Hay_Bone_Marrow_Pro_B: 	179 (16% of 1086)
	Hay_Bone_Marrow_Stromal: 	291 (17% of 1754)
	Aizarani_Liver_C1_NK_NKT_cells_1: 	26 (17% of 157)
	Aizarani_Liver_C2_Kupffer_Cells_1: 	7 (4% of 200)
	Aizarani_Liver_C3_NK_NKT_cells_2: 	21 (13% of 162)
	Aizarani_Liver_C4_EPCAM_pos_bile_duct_cells_1: 	10 (5% of 191)
	Aizarani_Liver_C5_NK_NKT_cells_3: 	25 (20% of 126)
	Aizarani_Liver_C6_Kupffer_Cells_2: 	14 (6% of 228)
	Aizarani_Liver_C7_EPCAM_pos_bile_duct_cells_2: 	11 (5% of 219)
	Aizarani_Liver_C8_Resident_B_cells_1: 	5 (14% of 35)
	Aizarani_Liver_C9_LSECs_1: 	22 (7% of 305)
	Aizarani_Liver_C10_MVECs_1: 	16 (6% of 270)
	Aizarani_Liver_C11_Hepatocytes_1: 	24 (8% of 298)
	Aizarani_Liver_C12_NK_NKT_cells_4: 	10 (20% of 49)
	Aizarani_Liver_C13_LSECs_2: 	24 (8% of 283)
	Aizarani_Liver_C14_Hepatocytes_2: 	21 (9% of 226)
	Aizarani_Liver_C17_Hepatocytes_3: 	8 (8% of 102)
	Aizarani_Liver_C18_NK_NKT_cells_5: 	6 (5% of 121)
	Aizarani_Liver_C20_LSECs_3: 	21 (7% of 296)
	Aizarani_Liver_C21_Stellate_cells_1: 	6 (3% of 195)
	Aizarani_Liver_C22_Resident_B_cells_2: 	5 (15% of 33)
	Aizarani_Liver_C23_Kupffer_Cells_3: 	14 (6% of 221)
	Aizarani_Liver_C24_EPCAM_pos_bile_duct_cells_3: 	7 (4% of 185)
	Aizarani_Liver_C25_Kupffer_Cells_4: 	7 (4% of 174)
	Aizarani_Liver_C28_NK_NKT_cells_6: 	10 (10% of 99)
	Aizarani_Liver_C29_MVECs_2: 	17 (5% of 314)
	Aizarani_Liver_C30_Hepatocytes_4: 	53 (12% of 445)
	Aizarani_Liver_C31_Kupffer_Cells_5: 	8 (7% of 120)
	Aizarani_Liver_C32_MVECs_3: 	3 (2% of 125)
	Aizarani_Liver_C33_Stellate_cells_2: 	5 (4% of 126)
	Aizarani_Liver_C34_MHC_II_pos_B_cells: 	13 (10% of 134)
	Aizarani_Liver_C38_Resident_B_cells_3: 	4 (17% of 23)
	Aizarani_Liver_C39_EPCAM_pos_bile_duct_cells_4: 	5 (3% of 184)
	Menon_Fetal_Kidney_0_Cap_Mesenchyme_Cells: 	9 (10% of 90)
	Menon_Fetal_Kidney_1_Embryonic_Red_Blood_Cells: 	35 (28% of 126)
	Menon_Fetal_Kidney_2_Nephron_Progenitor_Cells: 	5 (11% of 44)
	Menon_Fetal_Kidney_3_Stromal_Cells: 	3 (4% of 81)
	Menon_Fetal_Kidney_4_Podocytes: 	12 (6% of 206)
	Menon_Fetal_Kidney_5_Proximal_Tubule_Cells: 	15 (13% of 112)
	Menon_Fetal_Kidney_6_Collecting_Duct_Cells: 	4 (4% of 94)
	Menon_Fetal_Kidney_7_Loopof_Henle_Cells_Distal: 	49 (18% of 275)
	Menon_Fetal_Kidney_8_Connecting_Tubule_Cells: 	33 (12% of 267)
	Menon_Fetal_Kidney_9_Endothelial_Cells: 	7 (7% of 102)
	Menon_Fetal_Kidney_10_Immune_Cells: 	6 (7% of 83)
	Lake_Adult_Kidney_C1_Epithelial_Cells_unassigned: 	3 (10% of 30)
	Lake_Adult_Kidney_C2_Podocytes: 	11 (5% of 212)
	Lake_Adult_Kidney_C3_Proximal_Tubule_Epithelial_Cells_S1_S2: 	26 (12% of 221)
	Lake_Adult_Kidney_C4_Proximal_Tubule_Epithelial_Cells_S2: 	15 (9% of 176)
	Lake_Adult_Kidney_C5_Proximal_Tubule_Epithelial_Cells_Stress_Inflam: 	49 (12% of 417)
	Lake_Adult_Kidney_C6_Proximal_Tubule_Epithelial_Cells_Fibrinogen_pos_S3: 	7 (4% of 181)
	Lake_Adult_Kidney_C7_Proximal_Tubule_Epithelial_Cells_S3: 	5 (4% of 135)
	Lake_Adult_Kidney_C8_Decending_thin_Limb: 	12 (4% of 278)
	Lake_Adult_Kidney_C9_Thin_ascending_limb: 	12 (4% of 268)
	Lake_Adult_Kidney_C10_Thin_ascending_limb: 	22 (6% of 353)
	Lake_Adult_Kidney_C11_Thin_ascending_limb: 	8 (5% of 169)
	Lake_Adult_Kidney_C12_Thick_Ascending_Limb: 	33 (9% of 380)
	Lake_Adult_Kidney_C13_Thick_Ascending_Limb: 	14 (11% of 131)
	Lake_Adult_Kidney_C14_Distal_Convoluted_Tubule: 	13 (6% of 208)
	Lake_Adult_Kidney_C15_Connecting_Tubule: 	10 (6% of 171)
	Lake_Adult_Kidney_C16_Collecting_system_Principal_Cells_cortex: 	10 (7% of 141)
	Lake_Adult_Kidney_C17_Collecting_system_PCs_Stressed_Dissoc_Subset: 	9 (4% of 240)
	Lake_Adult_Kidney_C18_Collecting_Duct_Principal_Cells_medulla: 	18 (6% of 322)
	Lake_Adult_Kidney_C19_Collecting_Duct_Intercalated_Cells_Type_A_medulla: 	23 (7% of 326)
	Lake_Adult_Kidney_C20_Collecting_Duct_Intercalated_Cells_Type_A_cortex: 	14 (9% of 152)
	Lake_Adult_Kidney_C21_Collecting_Duct_Intercalated_Cells_Type_B: 	6 (6% of 103)
	Lake_Adult_Kidney_C22_Endothelial_Cells_glomerular_capillaries: 	4 (3% of 137)
	Lake_Adult_Kidney_C23_Endothelial_Cells_AVR: 	8 (6% of 126)
	Lake_Adult_Kidney_C24_Endothelial_Cells_AEA_and_DVR: 	4 (3% of 152)
	Lake_Adult_Kidney_C25_Endothelial_Cells_unassigned: 	1 (3% of 38)
	Lake_Adult_Kidney_C26_Mesangial_Cells: 	8 (5% of 177)
	Lake_Adult_Kidney_C27_Vascular_Smooth_Muscle_Cells_and_pericytes: 	7 (5% of 155)
	Lake_Adult_Kidney_C28_Interstitium: 	5 (6% of 86)
	Lake_Adult_Kidney_C29_Unknown_Novel_PT_CFH_pos_Subpopulation_S2: 	8 (9% of 86)
	Hu_Fetal_Retina_Amacrine: 	4 (6% of 64)
	Hu_Fetal_Retina_Bipolar: 	13 (15% of 86)
	Hu_Fetal_Retina_Blood: 	38 (13% of 282)
	Hu_Fetal_Retina_Fibroblast: 	24 (6% of 385)
	Hu_Fetal_Retina_Horizontal: 	6 (15% of 40)
	Hu_Fetal_Retina_Microglia: 	24 (6% of 382)
	Hu_Fetal_Retina_Muller: 	1 (2% of 42)
	Hu_Fetal_Retina_Photoreceptor: 	13 (18% of 71)
	Hu_Fetal_Retina_RGC: 	24 (5% of 443)
	Hu_Fetal_Retina_RPC: 	8 (7% of 107)
	Hu_Fetal_Retina_RPE: 	39 (13% of 292)
	Muraro_Pancreas_Alpha_Cell: 	39 (7% of 566)
	Muraro_Pancreas_Beta_Cell: 	50 (5% of 948)
	Muraro_Pancreas_Delta_Cell: 	14 (6% of 249)
	Muraro_Pancreas_Pancreatic_Polypeptide_Cell: 	9 (6% of 155)
	Muraro_Pancreas_Epsilon_Cell: 	1 (2% of 44)
	Muraro_Pancreas_Ductal_Cell: 	58 (5% of 1277)
	Muraro_Pancreas_Acinar_Cell: 	20 (3% of 731)
	Muraro_Pancreas_Mesenchymal_Stromal_Cell: 	25 (4% of 680)
	Muraro_Pancreas_Endothelial_Cell: 	18 (5% of 362)
Genes in the gene sets NOT available in the dataset: 
	Muraro_Pancreas_Alpha_Cell: 	39 (7% of 566)
	Muraro_Pancreas_Beta_Cell: 	50 (5% of 948)
	Muraro_Pancreas_Delta_Cell: 	14 (6% of 249)
	Muraro_Pancreas_Pancreatic_Polypeptide_Cell: 	9 (6% of 155)
	Muraro_Pancreas_Epsilon_Cell: 	1 (2% of 44)
	Muraro_Pancreas_Ductal_Cell: 	58 (5% of 1277)
	Muraro_Pancreas_Acinar_Cell: 	20 (3% of 731)
	Muraro_Pancreas_Mesenchymal_Stromal_Cell: 	25 (4% of 680)
	Muraro_Pancreas_Endothelial_Cell: 	18 (5% of 362)

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output file: sample-comparisons.knit.md

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output file: droplet-processing.knit.md

Warning messages:
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processing file: doublet-detection.Rmd

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Welcome to Bioconductor

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10 clusters
Creating ~5000 artifical doublets...
Dimensional reduction
Finding KNN...
Evaluating cell neighborhoods...
Training model...
iter=0, th=0.694, 68 cells
Threshold found:0.929
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output file: doublet-detection.knit.md

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Welcome to Bioconductor

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output file: cell-cycle.knit.md

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require("ensembldb")

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output file: trajectory.knit.md

There were 11 warnings (use warnings() to see them)
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computing terminal states
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processing file: nuclei-analysis.Rmd

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Welcome to Bioconductor

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output file: nuclei-analysis.knit.md



processing file: protein-abundance.Rmd

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output file: protein-abundance.knit.md

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output file: interactive.knit.md



processing file: big-data.Rmd

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Loading required package: SingleCellExperiment
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats

Attaching package: 'MatrixGenerics'

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Loading required package: GenomicRanges
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Attaching package: 'S4Vectors'

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Loading required package: IRanges
Loading required package: GenomeInfoDb
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: 'bluster'

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Quitting from lines 53-57 (big-data.Rmd) 
Error: rand > 0.9 is not TRUE

Execution halted
Error in Rscript_render(f, render_args, render_meta, add1, add2) : 
  Failed to compile big-data.Rmd
Calls: <Anonymous> -> render_new_session -> Rscript_render
Execution halted
make: *** [Makefile:4: compiled] Error 1
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  running 'make' failed
Execution halted