R Under development (unstable) (2025-04-26 r88181 ucrt) -- "Unsuffered Consequences"
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> library(testthat)
> library(rliger)
Package `rliger` has been updated massively since version 1.99.0, including the object structure which is not compatible with old versions.

We recommand you backup your old analysis before overwriting any existing result.

`readLiger()` is provided for reading an RDS file storing an old object and it converts the object to the up-to-date structure.
> 
> test_check("rliger")
Starting online iNMF scenario 1, factorize all datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
************************************************Total iterations:  30
Total time:        0 sec
Objective error:   37129
**|
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Reading input file...

Number of nodes: 600
Number of edges: 16900

Running Louvain algorithm...
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

Modularity: 0.7596
Number of communities: 9
Elapsed time: 0 seconds
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Reading input file...

Number of nodes: 600
Number of edges: 16701

Running Louvain algorithm...
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

Modularity: 0.7658
Number of communities: 10
Elapsed time: 0 seconds
Starting online iNMF scenario 1, factorize all datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
************************************************Total iterations:  30
Total time:        0 sec
Objective error:   37129
**|
Using method 'umap'
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Using method 'umap'
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Starting online iNMF scenario 1, factorize all datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
************************************************Total iterations:  30
Total time:        0 sec
Objective error:   37129
**|
Wilcoxon rank-sum test over 266 features across 300 cells
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Wilcoxon rank-sum test over 249 features across 600 cells
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Wilcoxon rank-sum test over 249 features across 116 cells
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Wilcoxon rank-sum test over 249 features across 89 cells
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Wilcoxon rank-sum test over 249 features across 68 cells
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Wilcoxon rank-sum test over 249 features across 65 cells
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Wilcoxon rank-sum test over 249 features across 60 cells
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Wilcoxon rank-sum test over 249 features across 58 cells
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Wilcoxon rank-sum test over 249 features across 48 cells
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Wilcoxon rank-sum test over 249 features across 36 cells
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Wilcoxon rank-sum test over 249 features across 30 cells
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Wilcoxon rank-sum test over 249 features across 30 cells
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Dataset 1:
 NPM1, SAT1, VIM, FTH1, BTG1, ISG15, GBP1, RSAD2, HSP90AB1 
Shared:
 NMB, ANXA1, GPR183, NDUFC2, GAPDH, VIM, EIF1, SRGN, JUNB, S100A10, TMSB4X, PABPC1, H3F3B, SAT1, HIST1H2AC, RGCC, ANXA2, RPLP1, LYZ, RPL18, HLA-A, RPS15A, TMEM66, RSAD2, UBC, HSPA8, MALAT1, RPLP0, RPS6, RPS12 
Dataset 2
 RSAD2, VIM, ISG15, GBP1, HSP90AB1, SAT1, NPM1, FTH1, BTG1 
Dataset 1:
 CD83, VIM, CXCR4, MARCKSL1, GAPDH, FTL, ISG15, GBP1, SELL, RSAD2, CXCL10, PLAC8, SOD2, SAT1, IFI27, CCL2, CCL8, CCL3, CCL4, APOBEC3A, TYMP 
Shared:
 RPL23A, RPS2, CD79A, RPL18A, RPL12, RPL13A, RPL3, RPL27A, RPS23, RPL15, RPLP0, RPL10, RPL19, RPS8, RPS4X, RPS5, RPL10A, RPL11, RPS19, RPL18, RPS3A, RPL34, RPS18, PTMA, RPL7, RPS6, RPS27, RPLP1, RPL32, RPL14 
Dataset 2
 PLAC8, GBP1, IFI27, TYMP, ISG15, SELL, RSAD2, CXCL10, SOD2, SAT1, CCL2, CCL8, CCL3, CCL4, APOBEC3A, MARCKSL1, CXCR4, CD83, VIM, GAPDH, FTL 
Dataset 1:
 FCGR3A, LGALS1, RPLP0, RPL18, RPS12, RPS3A, RPL23A, S100A4, ACTB, RPL7, ISG15, GBP1, RSAD2, SAT1, CCNH 
Shared:
 CST7, CHRNB1, NKG7, APOBEC3G, CLIC3, CXCR4, GNLY, HLA-A, CD7, HLA-C, GZMB, SRGN, BAK1, TMSB4X, NDUFC2, HLA-B, B2M, BTG1, JTB, CCNH, FOXN3, H2AFZ, UBC, CREM, MALAT1, PTMA, ANXA1, H3F3B, VIM, RABL5 
Dataset 2
 CCNH, ISG15, RSAD2, SAT1, GBP1, S100A4, FCGR3A, RPS3A, RPS12, ACTB, RPL7, RPLP0, RPL23A, RPL18, LGALS1 
Dataset 1:
 CXCL10, GBP1, PTMA, S100A10, CD14, LGALS1, TIMP1, FAM26F, RPS3A, RPL10A, RPL3, S100A6, H2AFZ, CCL3, S100A8, GPX1, IL8, HLA-DQA1, LGALS3, ISG15, RSAD2, CD83, HSPA1A, GIMAP7, IDO1, TXN, MS4A7, IFI27, CCL2, CCL8 
Shared:
 FCGR3A, MS4A7, VMO1, FAM26F, GBP1, CXCL10, TYROBP, PLAC8, FCER1G, TIMP1, S100A11, FTH1, SAT1, SOD2, JUNB, TMSB4X, TYMP, HLA-C, SRGN, HLA-B, B2M, ACTB, HLA-DPA1, CST3, RPS19, APOBEC3A, MALAT1, TMEM66, S100A4, H3F3B 
Dataset 2
 ISG15, IFI27, MS4A7, APOBEC3A, HSPA1A, GIMAP7, CD83, RSAD2, GBP1, CXCL10, FAM26F, IDO1, TXN, CCL2, CCL8, CCL3, S100A10, S100A8, S100A6, PTMA, GPX1, IL8, H2AFZ, RPS3A, CD14, HLA-DQA1, RPL10A, TIMP1, LGALS3, LGALS1 
Dataset 1:
 RPL10A, H2AFZ, GAPDH, PABPC1, ISG15, GBP1, CXCL10, CD83, SAT1, EIF1, HERC6 
Shared:
 MIR155HG, MYC, ID3, CD83, NPM1, HLA-DQA1, HSP90AB1, CCR7, CCL3, HLA-DRB1, HSPA8, EIF1, HLA-DRA, RPLP0, RPS5, CCL4, JTB, RPL14, RPS23, RPL19, RPL10A, RPL7, RPS12, RPL18A, RPS2, PTMA, CD74, RPL23A, RPS8, RPLP1 
Dataset 2
 GBP1, EIF1, CD83, CXCL10, HERC6, ISG15, SAT1, H2AFZ, RPL10A, PABPC1, GAPDH 
Dataset 1:
 RPS8, RPS23, RPL15, RPL21, RPL7, RPL13A, MARCKSL1, RPS3A, TIMP1, RPS6, RPS3, ISG15, GBP1, RSAD2, CXCL10, HSPA1A, FAM26F, HSPB1, IDO1, CREM, CCL8, APOBEC3A, APOBEC3G, TYMP, THRAP3 
Shared:
 CXCL3, SERPINB2, IL8, CCL7, CCL2, CTSL, CTSB, RABL5, ANXA5, CD63, SOD2, FCER1G, FTL, CSTB, CD14, ANXA2, CCL3, FTH1, VIM, NFKBIA, LGALS1, GAPDH, ANXA1, SRGN, LGALS3, S100A6, S100A9, H3F3B, TYMP, TIMP1 
Dataset 2
 CCL8, THRAP3, HSPA1A, TYMP, HSPB1, CREM, APOBEC3G, ISG15, GBP1, RSAD2, CXCL10, FAM26F, IDO1, APOBEC3A, MARCKSL1, RPS8, RPL15, RPS3A, RPS23, TIMP1, RPL7, RPS6, RPS3, RPL21, RPL13A 
Dataset 1:
 RSAD2, ISG15, APOBEC3A, CD14, GPX1, GAPDH, MARCKSL1, RPL10, JTB, RPS3A, RPL21, RPS5, SAT1, RPS27A, RPL3, RPS8, RPL32, RPL7, RPS12, RPL15, PABPC1, RPL11, RPLP0, RPL10A, IL8, RPL19, S100A8, S100A6, DUSP2, CXCR4 
Shared:
 RSAD2, ISG15, APOBEC3A, CCL8, CXCL10, CCL2, CTSB, IDO1, SOD2, ANXA5, TYMP, FTL, CD63, HSPA1A, GBP1, CSTB, CTSL, IFI27, C15orf48, FAM26F, CCL7, FCER1G, LGALS3, LGALS1, FTH1, S100A11, TYROBP, ANXA2, HSPB1, TIMP1 
Dataset 2
 IDO1, HSPA1A, CCL4, CCL7, NFKBIA, CCL3, CXCL10, FAM26F, IFI27, RPS19, HERC6, ISG15, RSAD2, HSPB1, SAT1, CCL2, CCL8, APOBEC3A, RPL11, MARCKSL1, RPS8, S100A8, S100A6, RPS27A, DUSP2, CXCR4, PTMA, RPL32, RPL15, RPL14 
Dataset 1:
 BIRC3, S100A6, FTH1, CCL8, ID3, HLA-DPB1, GAPDH, CD79A, FTL, ISG15, GBP1, SELL, RSAD2, CXCL10, PLAC8, HSP90AB1, GIMAP7, SAT1, CREM, HSPA8, IFI27, CCL2, CCR7, H3F3B, APOBEC3A, TYMP, HERC6 
Shared:
 TMEM66, RPL13, RPL31, LTB, RPS18, RPL34, RPL32, RPS14, SELL, RPL21, RPS6, RPS15A, RPS27A, RPS12, RPL7, RPL3, RPS4X, RPS3, RPS3A, RPL9, RPL10, RPL11, RPL13A, RPS19, RPL10A, PABPC1, RPS23, RPS8, RPL27A, RPS2 
Dataset 2
 GIMAP7, PLAC8, CCR7, IFI27, H3F3B, SELL, GBP1, ISG15, RSAD2, CXCL10, HSP90AB1, SAT1, CREM, HSPA8, CCL2, CCL8, APOBEC3A, TYMP, HERC6, ID3, S100A6, HLA-DPB1, FTH1, BIRC3, GAPDH, CD79A, FTL 
Dataset 1:
 TEX264, FTH1, VIM, CCNH, UBC, RGCC, ISG15, GBP1, RSAD2, CXCL10, PLAC8, CD74, SAT1, CD79A 
Shared:
 GIMAP7, RGCC, ACAT2, BTG1, THRAP3, RELB, LTB, H2AFZ, EIF2AK1, CXCR4, HERC6, BIRC3, SELL, HSPA8, GPR183, CCR7, BAK1, HIST1H2AC, CHCHD10, EIF1, HSPB1, RPS27, JTB, MALAT1, H3F3B, PTMA, TMEM66, HSP90AB1, ANXA1, HLA-B 
Dataset 2
 GBP1, RSAD2, RGCC, UBC, ISG15, CXCL10, PLAC8, CD74, SAT1, CD79A, TEX264, VIM, FTH1, CCNH 
Dataset 1:
 CD14, S100A8, IFI27, RPL31, RPL27A, RPL21, RPL7, GBP1, MARCKSL1, RPS8, S100A6, S100A4, RPS27A, IL1B, PTMA, RPL15, RPL14, GPX1, IL8, CXCL3, H2AFZ, RPL34, RPS3A, RPS23, RPL10A, RPS4X, RPS6, RPS3, GAPDH, RGCC 
Shared:
 MARCKSL1, TIMP1, C15orf48, SOD2, FTH1, CD63, ANXA5, CSTB, SRGN, GAPDH, FTL, TYROBP, FCER1G, S100A11, EIF1, IL8, LGALS1, TYMP, B2M, LGALS3, ANXA2, CTSB, VIM, TXN, S100A10, ACTB, CCL2, NFKBIA, LYZ, HLA-B 
Dataset 2
 TXN, CST3, IDO1, APOBEC3A, MARCKSL1, PLAC8, S100A6, S100A4, HERC6, RPL19, RPS3, ISG15, GBP1, SELL, RSAD2, CXCL10, HIST1H2AC, HLA-C, HSPA1A, FAM26F, HSPB1, SAT1, CTSL, BIRC3, IFI27, CCL2, CCL7, CCL8, CCR7, APOBEC3B 
Dataset 1:
 IDO1, CST7, VMO1, IL8, SAT1, RPS5, TYMP, LAGE3, CXCR4, TIMP1, RGCC, RPL3, ISG15, GBP1, S100A4, SELL, RSAD2, CXCL10, HSPA1A, HSP90AB1, FAM26F, HSPB1, CTSB, ANXA1, HSPA8, IFI27, CCL2, H3F3B, APOBEC3A, APOBEC3B 
Shared:
 HLA-DPA1, HLA-DPB1, HLA-DRA, CD74, HLA-DRB1, TXN, HLA-DQA1, IDO1, CST3, CCR7, CD83, ANXA2, GPR183, MARCKSL1, ACTB, BIRC3, LYZ, CST7, TMSB4X, C15orf48, S100A10, LGALS1, B2M, GPX1, CD79A, NFKBIA, H2AFZ, RELB, ISG15, HSPA1A 
Dataset 2
 CXCL10, HSPA1A, ISG15, FAM26F, HSPB1, HERC6, GBP1, S100A4, APOBEC3G, RSAD2, HSP90AB1, HSPA8, SELL, SAT1, CTSB, IDO1, ANXA1, IFI27, CCL2, H3F3B, APOBEC3A, APOBEC3B, TYMP, CXCR4, IL8, TIMP1, RGCC, VMO1, CST7, RPS5 
Dataset 1:
 H3F3B, BIRC3, ISG15, HLA-C 
Shared:
 DUSP2, JUNB, GADD45B, HIST1H2AC, MYC, NFKBIA, BIRC3, BTG1, GZMK, CD83, PABPC1, APOBEC3G, TMEM66, H3F3B, EIF1, PTMA, UBC, HLA-C, NDUFC2, RPS19, GPR183, MALAT1, RPS5, RPL18, HLA-A, RPL19, RPS27, SRGN, RPL3, RPL27A 
Dataset 2
 HLA-C, ISG15, BIRC3, H3F3B 
Dataset 1:
 GAPDH, RPL12, FTL, ISG15, FCER1G, RSAD2, TYMP 
Shared:
 GZMH, FGFBP2, CCL5, CLIC3, NKG7, GZMB, CST7, GZMK, HLA-B, APOBEC3G, B2M, HLA-C, PTMA, TMSB4X, NDUFC2, RGCC, ANXA1, HLA-A, GAPDH, ACTN1, PLAC8, RPS19, MALAT1, RPL15, JTB, KLRD1, RPS3, TMEM66, RPS15A, RPL3 
Dataset 2
 TYMP, FCER1G, ISG15, RSAD2, RPL12, GAPDH, FTL 
Dataset 1:
 CCL2, H2AFZ, CD14, CTSL, RPL10A, RPS8, RPS6, TIMP1, S100A8, RPS27, RPLP0, RPL21, RPL14, RPL34, RPL7, RPL18A, ID3, RPL11, MARCKSL1, RPL31, IL1B, RPL15, RPL9, IL8, RPS3A, RPS14, NPM1, RPS4X, RPL10, PABPC1 
Shared:
 S100A4, LGALS3, CTSL, S100A6, GPX1, S100A11, FTL, S100A10, LGALS1, CTSB, CST3, FCER1G, ACTB, VIM, ANXA2, CD63, TYMP, TYROBP, CSTB, HLA-DRB1, CCL2, FCGR3A, ANXA1, ANXA5, SAT1, ACTN1, JTB, HLA-DRA, HLA-DPB1, H3F3B 
Dataset 2
 HSPB1, FAM26F, LYZ, HSPA1A, RPS14, RPL9, HIST1H2AC, HLA-A, APOBEC3A, ISG15, GBP1, RSAD2, CXCL10, HLA-C, HSP90AB1, SAT1, IDO1, CTSL, TXN, CREM, CCL2, CCL7, CCL8, APOBEC3B, APOBEC3G, TYMP, HERC6, ID3, RPL11, MARCKSL1 
Dataset 1:
 HSPA1A, H3F3B, CXCR4, FTL, ISG15, GBP1, RSAD2, RPL34, HLA-A, HLA-C, HLA-B, RPLP1, RPS2 
Shared:
 UBC, HSPA1A, GADD45G, GADD45B, HSP90AB1, HSPA8, HSPB1, H3F3B, PPBP, CREM, SAT1, BIRC3, CCNH, EIF1, NFKBIA, H2AFZ, JUNB, ID3, TMEM66, BTG1, MALAT1, RPS27, HIST1H2AC, NPM1, GBP1, CXCR4, RPS12, RPL14, RELB, CXCL10 
Dataset 2
 GBP1, RPLP1, HLA-C, RSAD2, HLA-B, ISG15, RPL34, HLA-A, RPS2, CXCR4, HSPA1A, H3F3B, FTL 
Dataset 1:
 CXCL3, IL8, FTH1, RPL9, GBP1, MARCKSL1, IL1B, H2AFZ, CD14, ISG15, RSAD2, CXCL10, HIST1H2AC, HSPA1A, FAM26F, HSPB1, SAT1, IDO1, CCL8, CST3, APOBEC3A, APOBEC3G 
Shared:
 IL1B, LYZ, IL8, CST3, NFKBIA, CCL3, S100A10, APOBEC3B, GPX1, ACTB, C15orf48, ANXA2, S100A6, S100A4, HLA-DPB1, CCL4, CXCL3, HLA-DRA, HLA-DRB1, S100A11, TYROBP, IFI27, JTB, HLA-DPA1, VIM, FCER1G, CD74, SRGN, ANXA1, HBA1 
Dataset 2
 FAM26F, CXCL10, CST3, HSPA1A, IL1B, SAT1, IDO1, ISG15, GBP1, RSAD2, HIST1H2AC, HSPB1, CCL8, APOBEC3A, APOBEC3G, MARCKSL1, RPL9, IL8, CXCL3, H2AFZ, CD14, FTH1 
Dataset 1:
 APOBEC3B, IL8, S100A4, MARCKSL1, RPS27A, RPL15, RPL7, RPL12, S100A9, PABPC1, S100A8, IL1B, TIMP1, RPS6, BTG1, RPLP0, RGCC, RPL13A, RPL3, ISG15, GBP1, RSAD2, CXCL10, HIST1H2AC, HSPA1A, FAM26F, HSPB1, SAT1, CTSB, IDO1 
Shared:
 S100A8, S100A9, CD14, GPX1, APOBEC3B, S100A6, TYROBP, LGALS1, S100A4, TYMP, S100A10, IL8, MS4A7, S100A11, FTL, NFKBIA, FTH1, MARCKSL1, APOBEC3A, FCER1G, LYZ, SRGN, SAT1, GAPDH, C15orf48, ANXA5, ACTB, CTSB, ISG15, CD63 
Dataset 2
 CCL2, HIST1H2AC, S100A8, IDO1, CCL8, CCL7, FAM26F, CTSB, CST3, HSPA1A, APOBEC3G, HSPB1, ISG15, GBP1, RSAD2, CXCL10, SAT1, CTSL, TXN, LGALS3, APOBEC3A, APOBEC3B, MARCKSL1, S100A9, S100A4, RPS27A, IL1B, RPL15, IL8, TIMP1 
Dataset 1:
 GAPDH, VIM, ACTB, S100A6, TIMP1, RGCC, ISG15, CXCL10, HLA-DPA1, CREM, CD79A 
Shared:
 RBM10, GZMK, LAGE3, ACAT2, NDUFC2, RPL14, CHCHD10, HSP90AB1, RPLP0, APOBEC3A, RPL12, RSAD2, RPL18A, GAPDH, CSTB, RPS3, RPS6, NPM1, RPL18, RPS15A, RPS19, TMSB4X, RPS12, HLA-A, TYMP, RPS3A, CCL5, RPL15, CD14, LGALS3 
Dataset 2
 CREM, HLA-DPA1, ISG15, CXCL10, CD79A, S100A6, ACTB, TIMP1, VIM, GAPDH, RGCC 
Dataset 1:
 TMEM66, BTG1, ISG15, RSAD2, SAT1, ANXA1, HERC6 
Shared:
 KLRC1, KLRD1, GNLY, APOBEC3G, NKG7, CD7, GZMB, HLA-A, PLAC8, PPBP, LAGE3, CCL5, GPR183, SRGN, HLA-B, TEX264, THRAP3, EIF2AK1, B2M, TMSB4X, CD63, HLA-C, RPL9, XCL2, RPS27A, CXCR4, RPS3, RPLP1, H3F3B, ACTB 
Dataset 2
 ANXA1, HERC6, ISG15, RSAD2, SAT1, TMEM66, BTG1 
Starting online iNMF scenario 1, factorize all datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
************************************************Total iterations:  30
Total time:        0 sec
Objective error:   37129
**|
Starting online iNMF scenario 1, factorize all datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Total iterations:  42
Total time:        0 sec
Objective error:   59878.9
INMF started, niter=2
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Total time:      0 sec
Objective error: 49910.7
UINMF started, niter=2
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Total time:      0 sec
Objective error: 4377.62
UINMF started, niter=2
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Total time:      0 sec
Objective error: 4629.63
UINMF started, niter=2
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Total time:      0 sec
Objective error: 11026.4
Starting online iNMF scenario 1, factorize all datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
************************************************Total iterations:  30
Total time:        0 sec
Objective error:   45414.7
**|
INMF started, niter=2
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Total time:      0 sec
Objective error: 41528.3
INMF started, niter=2
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Total time:      0 sec
Objective error: 47418.4
INMF started, niter=2
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Total time:      0 sec
Objective error: 45693.4
INMF started, niter=2
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Total time:      0 sec
Objective error: 45973.6
INMF started, niter=2
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Total time:      0 sec
Objective error: 22149.3
INMF started, niter=2
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Total time:      0 sec
Objective error: 66227.2
INMF started, niter=2
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Total time:      0 sec
Objective error: 66117.9
Starting online iNMF scenario 1, factorize all datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
************************************************Total iterations:  30
Total time:        0 sec
Objective error:   37129
**|
Starting online iNMF scenario 2, update factorization with new datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**********************************************Total iterations:  15
Total time:        0 sec
Objective error:   54366.5
****|
Starting online iNMF scenario 2, update factorization with new datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**********************************************Total iterations:  15
Total time:        0 sec
Objective error:   54366.5
****|
Starting online iNMF scenario 1, factorize all datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
************************************************Total iterations:  30
Total time:        0 sec
Objective error:   37129
**|
Starting online iNMF scenario 1, factorize all datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
************************************************Total iterations:  30
Total time:        0 sec
Objective error:   37129
**|
INMF started, niter=30
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Total time:      0 sec
Objective error: 35967.3
INMF started, niter=30
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Total time:      0 sec
Objective error: 35967.3
Starting online iNMF scenario 1, factorize all datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
************************************************Total iterations:  30
Total time:        0 sec
Objective error:   45479.1
**|
INMF started, niter=2
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Total time:      0 sec
Objective error: 49910.7
completed constructor::A::173x300
time taken:0.497274
completed constructor::A::173x300
time taken:0.518517
completed constructor::A::173x300
time taken:0.493211
completed constructor::A::173x300
time taken:0.521668
completed constructor::A::173x300
time taken:0.496322
completed constructor::A::173x300
time taken:0.523248
Working ctrl H5 file path:  D:\temp\2025_04_29_20_55_16_13910\RtmpWcPBQG\ctrltest_e3d865974e89.h5 
Working stim H5 file path:  D:\temp\2025_04_29_20_55_16_13910\RtmpWcPBQG\stimtest_e3d855a1643f.h5 
Starting online iNMF scenario 1, factorize all datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
************************************************Total iterations:  30
Total time:        0 sec
Objective error:   45414.7
**|
Using method 'umap'
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
A liger command record, performed at 04-29-2025 15:08:33 EDT 
Call: normalize.liger(object) 
Parameters:
    useDatasets : "ctrl", "stim" 
    verbose : TRUE 
Starting online iNMF scenario 1, factorize all datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
************************************************Total iterations:  30
Total time:        0 sec
Objective error:   45414.7
**|
Using method 'umap'
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Working ctrl H5 file path:  D:\temp\2025_04_29_20_55_16_13910\RtmpWcPBQG\ctrltest_e3d8350e49f1.h5 
Working stim H5 file path:  D:\temp\2025_04_29_20_55_16_13910\RtmpWcPBQG\stimtest_e3d821c5517e.h5 
Starting online iNMF scenario 1, factorize all datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
************************************************Total iterations:  30
Total time:        0 sec
Objective error:   45414.7
**|
Using method 'umap'
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
An object of class ligerDataset with 300 cells
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%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%
Working ctrl H5 file path:  D:\temp\2025_04_29_20_55_16_13910\RtmpWcPBQG\ctrltest_e3d8258948aa.h5 
Working stim H5 file path:  D:\temp\2025_04_29_20_55_16_13910\RtmpWcPBQG\stimtest_e3d823b9565.h5 
Working ctrl H5 file path:  D:\temp\2025_04_29_20_55_16_13910\RtmpWcPBQG\ctrltest_e3d8520166db.h5 
Working stim H5 file path:  D:\temp\2025_04_29_20_55_16_13910\RtmpWcPBQG\stimtest_e3d868213e00.h5 
Working ctrl H5 file path:  D:\temp\2025_04_29_20_55_16_13910\RtmpWcPBQG\ctrltest_e3d8379418ff.h5 
Working stim H5 file path:  D:\temp\2025_04_29_20_55_16_13910\RtmpWcPBQG\stimtest_e3d83dda3a27.h5 
Working ctrl H5 file path:  D:\temp\2025_04_29_20_55_16_13910\RtmpWcPBQG\ctrltest_e3d8284c68db.h5 
Working stim H5 file path:  D:\temp\2025_04_29_20_55_16_13910\RtmpWcPBQG\stimtest_e3d829f41d87.h5 
Starting online iNMF scenario 1, factorize all datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
************************************************Total iterations:  30
Total time:        0 sec
Objective error:   37129
**|
Using method 'umap'
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
Working ctrl H5 file path:  D:\temp\2025_04_29_20_55_16_13910\RtmpWcPBQG\ctrltest_e3d817b8902.h5 
Working stim H5 file path:  D:\temp\2025_04_29_20_55_16_13910\RtmpWcPBQG\stimtest_e3d852a3af1.h5 
Starting online iNMF scenario 1, factorize all datasets
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
************************************************Total iterations:  30
Total time:        0 sec
Objective error:   37129
**|
Using method 'umap'
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|

[ FAIL 0 | WARN 2 | SKIP 1 | PASS 1363 ]

══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• {fields} is not installed (1): 'test_preprocessing.R:113:5'

[ FAIL 0 | WARN 2 | SKIP 1 | PASS 1363 ]
> 
> proc.time()
   user  system elapsed 
 147.39    3.57  467.37