Error using IntegrateLayers()

[sguttr]

I am trying to run integrate layers:

Dataset <- IntegrateLayers(object = Dataset, method = CCAIntegration, orig.reduction = "pca", new.reduction = "integrated.cca", dims = 1, verbose = FALSE)

(My dimensions are 1 due to some samples having two cells in them)

I keep getting this error:

Warning in irlba(A = mat3, nv = num.cc) : You're computing too large a percentage of total singular values, use a standard svd instead. Warning: No columnames present in cell embeddings, setting to 'CC_1:' Error in 1:ncol(x = embeddings) : argument of length 0

How do I rectify this?

My session info is:

`R version 4.4.0 (2024-04-24)
Platform: x86_64-apple-darwin20
Running under: macOS 15.1

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0

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: Europe/London
tzcode source: internal

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

other attached packages:
[1] patchwork_1.3.0 Seurat_5.1.0 SeuratObject_5.0.2 sp_2.1-4 dplyr_1.1.4

loaded via a namespace (and not attached):
[1] deldir_2.0-4 pbapply_1.7-2 gridExtra_2.3 rlang_1.1.4
[5] magrittr_2.0.3 RcppAnnoy_0.0.22 spatstat.geom_3.3-3 matrixStats_1.4.1
[9] ggridges_0.5.6 compiler_4.4.0 png_0.1-8 vctrs_0.6.5
[13] reshape2_1.4.4 stringr_1.5.1 pkgconfig_2.0.3 fastmap_1.2.0
[17] labeling_0.4.3 utf8_1.2.4 promises_1.3.0 rmarkdown_2.29
[21] purrr_1.0.2 xfun_0.49 jsonlite_1.8.9 goftest_1.2-3
[25] later_1.3.2 spatstat.utils_3.1-1 irlba_2.3.5.1 parallel_4.4.0
[29] cluster_2.1.6 R6_2.5.1 ica_1.0-3 stringi_1.8.4
[33] RColorBrewer_1.1-3 spatstat.data_3.1-2 reticulate_1.39.0 parallelly_1.39.0
[37] spatstat.univar_3.1-1 lmtest_0.9-40 scattermore_1.2 Rcpp_1.0.13-1
[41] knitr_1.49 tensor_1.5 future.apply_1.11.3 zoo_1.8-12
[45] sctransform_0.4.1 httpuv_1.6.15 Matrix_1.7-1 splines_4.4.0
[49] igraph_2.1.1 tidyselect_1.2.1 abind_1.4-8 rstudioapi_0.17.1
[53] yaml_2.3.10 spatstat.random_3.3-2 codetools_0.2-20 miniUI_0.1.1.1
[57] spatstat.explore_3.3-3 listenv_0.9.1 lattice_0.22-6 tibble_3.2.1
[61] plyr_1.8.9 withr_3.0.2 shiny_1.9.1 ROCR_1.0-11
[65] evaluate_1.0.1 Rtsne_0.17 future_1.34.0 fastDummies_1.7.4
[69] survival_3.7-0 polyclip_1.10-7 fitdistrplus_1.2-1 pillar_1.9.0
[73] KernSmooth_2.23-24 plotly_4.10.4 generics_0.1.3 RcppHNSW_0.6.0
[77] ggplot2_3.5.1 munsell_0.5.1 scales_1.3.0 globals_0.16.3
[81] xtable_1.8-4 glue_1.8.0 lazyeval_0.2.2 tools_4.4.0
[85] data.table_1.16.2 RSpectra_0.16-2 RANN_2.6.2 leiden_0.4.3.1
[89] dotCall64_1.2 cowplot_1.1.3 grid_4.4.0 tidyr_1.3.1
[93] colorspace_2.1-1 nlme_3.1-166 cli_3.6.3 spatstat.sparse_3.1-0
[97] spam_2.11-0 fansi_1.0.6 viridisLite_0.4.2 uwot_0.2.2
[101] gtable_0.3.6 digest_0.6.37 progressr_0.15.0 ggrepel_0.9.6
[105] htmlwidgets_1.6.4 farver_2.1.2 htmltools_0.5.8.1 lifecycle_1.0.4
[109] httr_1.4.7 mime_0.12 MASS_7.3-61`

[rharao]

My dimensions are 1 due to some samples having two cells in them

What does this mean, experimentally? Could you show us the result of table(Dataset$orig.ident) (or whatever the grouping variable is by which the samples are separated)?