Unconstrained integration error - "more elements supplied than there are to replace"

[LacquerHed]

Hi I am running unconstrained integration and getting the following error, which seems to stem from the slots/layers ArchR is pulling from the seRNA (Seurat object) input.

2024-03-14 12:11:53.67366 : Block (1 of 1) : Imputing GeneScoreMatrix, 0.323 mins elapsed. Getting ImputeWeights Warning: Data is of class dgeMatrix. Coercing to dgCMatrix. Error in slot(object = object, name = "features")[[layer]] <- features : more elements supplied than there are to replace

This is happening with Seurat V5 objects but also V4 when I downgraded to that, so not sure if its the new layer structure of Seurat V5. Not sure how to limit elements supplied from the seRNA. Thanks.

ArchR-addGeneIntegrationMatrix-129a04b8342d3-Date-2024-03-14_Time-12-11-30.735514.log

sessionInfo()
R version 4.3.2 (2023-10-31)
Platform: x86_64-apple-darwin20 (64-bit)
Running under: macOS Sonoma 14.3.1
Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRlapack.dylib;  LAPACK version 3.11.0
Random number generation:
 RNG:     L'Ecuyer-CMRG 
 Normal:  Inversion 
 Sample:  Rejection 
 locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: America/New_York
tzcode source: internal

attached base packages:
 [1] parallel  stats4    grid      stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] harmony_1.2.0                      uwot_0.1.16                        nabor_0.5.0                       
 [4] Rsamtools_2.18.0                   BSgenome.Mmusculus.UCSC.mm10_1.4.3 BSgenome_1.70.2                   
 [7] rtracklayer_1.62.0                 BiocIO_1.12.0                      Biostrings_2.70.2                 
[10] XVector_0.42.0                     rhdf5_2.46.1                       SummarizedExperiment_1.32.0       
[13] Biobase_2.62.0                     MatrixGenerics_1.14.0              Rcpp_1.0.12                       
[16] Matrix_1.6-5                       GenomicRanges_1.54.1               GenomeInfoDb_1.38.7               
[19] IRanges_2.36.0                     S4Vectors_0.40.2                   BiocGenerics_0.48.1               
[22] matrixStats_1.2.0                  data.table_1.15.2                  stringr_1.5.1                     
[25] plyr_1.8.9                         magrittr_2.0.3                     gtable_0.3.4                      
[28] gtools_3.9.5                       gridExtra_2.3                      ArchR_1.0.2                       
[31] sctransform_0.4.1                  ggplot2_3.5.0                      dplyr_1.1.4                       
[34] Seurat_5.0.2                       SeuratObject_5.0.1                 sp_2.1-3                          

loaded via a namespace (and not attached):
  [1] RcppAnnoy_0.0.22          splines_4.3.2             later_1.3.2               bitops_1.0-7             
  [5] tibble_3.2.1              R.oo_1.26.0               polyclip_1.10-6           XML_3.99-0.16.1          
  [9] fastDummies_1.7.3         lifecycle_1.0.4           doParallel_1.0.17         globals_0.16.3           
 [13] lattice_0.22-5            MASS_7.3-60.0.1           limma_3.58.1              plotly_4.10.4            
 [17] yaml_2.3.8                httpuv_1.6.14             glmGamPoi_1.14.3          spam_2.10-0              
 [21] spatstat.sparse_3.0-3     reticulate_1.35.0         cowplot_1.1.3             pbapply_1.7-2            
 [25] RColorBrewer_1.1-3        abind_1.4-5               zlibbioc_1.48.0           Rtsne_0.17               
 [29] purrr_1.0.2               presto_1.0.0              R.utils_2.12.3            RCurl_1.98-1.14          
 [33] circlize_0.4.16           GenomeInfoDbData_1.2.11   ggrepel_0.9.5             irlba_2.3.5.1            
 [37] listenv_0.9.1             spatstat.utils_3.0-4      pheatmap_1.0.12           goftest_1.2-3            
 [41] RSpectra_0.16-1           spatstat.random_3.2-3     fitdistrplus_1.1-11       parallelly_1.37.1        
 [45] DelayedMatrixStats_1.24.0 leiden_0.4.3.1            codetools_0.2-19          DelayedArray_0.28.0      
 [49] tidyselect_1.2.1          shape_1.4.6.1             farver_2.1.1              spatstat.explore_3.2-6   
 [53] GenomicAlignments_1.38.2  jsonlite_1.8.8            GetoptLong_1.0.5          ellipsis_0.3.2           
 [57] progressr_0.14.0          ggridges_0.5.6            survival_3.5-8            iterators_1.0.14         
 [61] foreach_1.5.2             tools_4.3.2               ica_1.0-3                 glue_1.7.0               
 [65] SparseArray_1.2.4         withr_3.0.0               fastmap_1.1.1             rhdf5filters_1.14.1      
 [69] fansi_1.0.6               digest_0.6.35             R6_2.5.1                  mime_0.12                
 [73] colorspace_2.1-0          Cairo_1.6-2               scattermore_1.2           tensor_1.5               
 [77] spatstat.data_3.0-4       R.methodsS3_1.8.2         RhpcBLASctl_0.23-42       utf8_1.2.4               
 [81] tidyr_1.3.1               generics_0.1.3            httr_1.4.7                htmlwidgets_1.6.4        
 [85] S4Arrays_1.2.1            pkgconfig_2.0.3           ComplexHeatmap_2.18.0     lmtest_0.9-40            
 [89] htmltools_0.5.7           dotCall64_1.1-1           clue_0.3-65               scales_1.3.0             
 [93] png_0.1-8                 rstudioapi_0.15.0         reshape2_1.4.4            rjson_0.2.21             
 [97] nlme_3.1-164              zoo_1.8-12                GlobalOptions_0.1.2       KernSmooth_2.23-22       
[101] miniUI_0.1.1.1            vipor_0.4.7               restfulr_0.0.15           ggrastr_1.0.2            
[105] pillar_1.9.0              vctrs_0.6.5               RANN_2.6.1                promises_1.2.1           
[109] xtable_1.8-4              cluster_2.1.6             beeswarm_0.4.0            cli_3.6.2                
[113] compiler_4.3.2            rlang_1.1.3               crayon_1.5.2              future.apply_1.11.1      
[117] labeling_0.4.3            ggbeeswarm_0.7.2          stringi_1.8.3             BiocParallel_1.36.0      
[121] viridisLite_0.4.2         deldir_2.0-4              munsell_0.5.0             lazyeval_0.2.2           
[125] spatstat.geom_3.2-9       RcppHNSW_0.6.0            patchwork_1.2.0           sparseMatrixStats_1.14.0 
[129] future_1.33.1             Rhdf5lib_1.24.2           statmod_1.5.0             shiny_1.8.0              
[133] ROCR_1.0-11               igraph_2.0.3`

[rcorces]

Hi @LacquerHed! Thanks for using ArchR! Lately, it has been very challenging for me to keep up with maintenance of this package and all of my other
responsibilities as a PI. I have not been responding to issue posts and I have not been pushing updates to the software. We are actively searching to hire
a computational biologist to continue to develop and maintain ArchR and related tools. If you know someone who might be a good fit, please let us know!
In the meantime, your issue will likely go without a reply. Most issues with ArchR right not relate to compatibility. Try reverting to R 4.1 and Bioconductor 3.15.
Newer versions of Seurat and Matrix also are causing issues. Sorry for not being able to provide active support for this package at this time.

[zvittorio]

Hi @LacquerHed

I had the same error, in the same step. This is my code (the part that generates the error)

seRNA = readRDS("scRNA-Hematopoiesis-Granja-2019.rds")
seurObj = CreateSeuratObject(counts = CreateAssayObject(assay(seRNA)), meta.data = as.data.frame(colData(seRNA)))

Project = addGeneIntegrationMatrix(
    ArchRProj = Project, 
    useMatrix = "GeneScoreMatrix",
    matrixName = "GeneIntegrationMatrix",
    reducedDims = "IterativeLSI",
    seRNA = seurObj,
    addToArrow = FALSE,
    groupRNA = "BioClassification", 
    nameCell = "predictedCell_Un", 
    nameGroup = "predictedGroup_Un",
    nameScore = "predictedScore_Un"
)

I was running on R-4.3.2 with ArchR-1.0.2.
Reverting to an older R version (4.2.2) as suggested by @rcorces does not generate the error and the function runs smoothly. I hope this helps, also on the dev side for further fixes ;)

[jiangpuxuan]

Try update your seurat to 5 , archR to 1.0.3
and bioconductor to 3.19

And try to run Rscript in your shell rather than using rstudio !

[jiangpuxuan]

Hi @LacquerHed

I had the same error, in the same step. This is my code (the part that generates the error)

seRNA = readRDS("scRNA-Hematopoiesis-Granja-2019.rds")
seurObj = CreateSeuratObject(counts = CreateAssayObject(assay(seRNA)), meta.data = as.data.frame(colData(seRNA)))

Project = addGeneIntegrationMatrix(
    ArchRProj = Project, 
    useMatrix = "GeneScoreMatrix",
    matrixName = "GeneIntegrationMatrix",
    reducedDims = "IterativeLSI",
    seRNA = seurObj,
    addToArrow = FALSE,
    groupRNA = "BioClassification", 
    nameCell = "predictedCell_Un", 
    nameGroup = "predictedGroup_Un",
    nameScore = "predictedScore_Un"
)

I was running on R-4.3.2 with ArchR-1.0.2. Reverting to an older R version (4.2.2) as suggested by @rcorces does not generate the error and the function runs smoothly. I hope this helps, also on the dev side for further fixes ;)

I have once been doubted by the same error but it works with latest seurat archr bioconductor.

[KyriakisDimitrios]

Getting the same error with the latest seurat and archR

R version 4.2.2 (as suggested)
Seurat_5.1.0                
SeuratObject_5.0.2
ArchR_1.0.2    

2024-06-07 10:13:24 : Block (1 of 67) : Imputing GeneScoreMatrix, 2.501 mins elapsed.
Getting ImputeWeights
Warning: Data is of class dgeMatrix. Coercing to dgCMatrix.
Error in slot(object = object, name = "features")[[layer]] <- features : 
  more elements supplied than there are to replace
Calls: addGeneIntegrationMatrix ... .CreateStdAssay.list -> LayerData<- -> LayerData<-.Assay5
Execution halted

[KyriakisDimitrios]

Hi @LacquerHed
I had the same error, in the same step. This is my code (the part that generates the error)

seRNA = readRDS("scRNA-Hematopoiesis-Granja-2019.rds")
seurObj = CreateSeuratObject(counts = CreateAssayObject(assay(seRNA)), meta.data = as.data.frame(colData(seRNA)))

Project = addGeneIntegrationMatrix(
    ArchRProj = Project, 
    useMatrix = "GeneScoreMatrix",
    matrixName = "GeneIntegrationMatrix",
    reducedDims = "IterativeLSI",
    seRNA = seurObj,
    addToArrow = FALSE,
    groupRNA = "BioClassification", 
    nameCell = "predictedCell_Un", 
    nameGroup = "predictedGroup_Un",
    nameScore = "predictedScore_Un"
)

I was running on R-4.3.2 with ArchR-1.0.2. Reverting to an older R version (4.2.2) as suggested by @rcorces does not generate the error and the function runs smoothly. I hope this helps, also on the dev side for further fixes ;)

I have once been doubted by the same error but it works with latest seurat archr bioconductor.

Can you share the exact version?

Here is mine
R version 4.2.2 (as suggested)
Seurat_5.1.0
SeuratObject_5.0.2
ArchR_1.0.2

And still, I get the same error.
Thanks

[zvittorio]

Hi @KyriakisDimitrios

We later found out that the change that fixed the problem was actually reverting Seurat (and SeuratObject) to version 4.3, which in our case came together with reverting R version automatically, since we are using software modules on a cluster.
With this change, we were able to keep the latest R version but with older Seurat.

[jiangpuxuan]

Guys you should test addintegratedmatrix step by step
some function in addintegratedmatrix from Seurat should use v4 and some v5

[wgao688]

Hi @KyriakisDimitrios , I'm wondering if you solved this issue since I am also experiencing the same issue despite the suggestions here. I have tried using an SCE and Seurat object but it results the same error. Thanks!

[KyriakisDimitrios]

Hi @KyriakisDimitrios , I'm wondering if you solved this issue since I am also experiencing the same issue despite the suggestions here. I have tried using an SCE and Seurat object but it results the same error. Thanks!

Hi @wgao688,
I solved the issue using @jiangpuxuan's suggestion. I ran the function step by step and identified the problem in the 4th step: Begin Integration. This step is split into 4 substeps.
I used Seurat v5 for steps 1 and 2 (Create Seurat RNA and Normalize, Get Gene Score Matrix, and Create Seurat ATAC) and Seurat v4 for steps 3 and 4 (Transfer Anchors, Transfer Data).

[ZhangFuchang]

After repeated testing, I finally know the answer to this question：

This error occurred in the RNAIntegration.R of the ArchR package
This code in the RNAIntegration.R file:
seuratATAC <- Seurat::CreateSeuratObject(counts = mat[head(seq_len(nrow(mat)), 5), , drop = FALSE])

The Seurat::CreateSeuratObject function requires that the rownames of mat must be vector, not matrix. But the rownames passed to mat in the previous code was actually a matrix, so you only need to add a command line before this code, this will cast the rownames of mat to a vector:

rownames(mat) <- as.character(rownames(mat))

And then this error was completely eliminated.

[ZhangFuchang]

After repeated testing, I finally know the answer to this question：

This error occurred in the RNAIntegration.R of the ArchR package
This code in the RNAIntegration.R file:
seuratATAC <- Seurat::CreateSeuratObject(counts = mat[head(seq_len(nrow(mat)), 5), , drop = FALSE])

The Seurat::CreateSeuratObject function requires that the rownames of the mat must be vector, not matrix. But the rownames passed to the mat in the previous code was actually a matrix, so you only need to add a command line before this code, this will cast the rownames of mat to a vector:

rownames(mat) <- as.character(rownames(mat))

And then this error was completely eliminated.

[joeyQX]

After repeated testing, I finally know the answer to this question：

This error occurred in the RNAIntegration.R of the ArchR package This code in the RNAIntegration.R file: seuratATAC <- Seurat::CreateSeuratObject(counts = mat[head(seq_len(nrow(mat)), 5), , drop = FALSE])

The Seurat::CreateSeuratObject function requires that the rownames of mat must be vector, not matrix. But the rownames passed to mat in the previous code was actually a matrix, so you only need to add a command line before this code, this will cast the rownames of mat to a vector:

rownames(mat) <- as.character(rownames(mat))

And then this error was completely eliminated.

Thxs but where is the RNAIntegration.R file? How to modify the code of the addGeneIntegrationMatrix function? I try to edit the code of ArchR but didn't figure out.

[ZhangFuchang]

After repeated testing, I finally know the answer to this question：
This error occurred in the RNAIntegration.R of the ArchR package This code in the RNAIntegration.R file: seuratATAC <- Seurat::CreateSeuratObject(counts = mat[head(seq_len(nrow(mat)), 5), , drop = FALSE])
The Seurat::CreateSeuratObject function requires that the rownames of mat must be vector, not matrix. But the rownames passed to mat in the previous code was actually a matrix, so you only need to add a command line before this code, this will cast the rownames of mat to a vector:
rownames(mat) <- as.character(rownames(mat))
And then this error was completely eliminated.

Thxs but where is the RNAIntegration.R file? How to modify the code of the addGeneIntegrationMatrix function? I try to edit the code of ArchR but didn't figure out.

I guess you should have installed the ArchR package on Windows or the compiled ArchR package on Linux.
So I suggest you download the source code package first, and never download the compiled package.
Then enter to the directory of the source code of ArchR:
ArchR/R/IntegrativeAnalysis.R
Modify it according to the method I proposed earlier.
Then install the modified source code again.
As for the method of installing from the source code, please search on Google or Baidu yourself.