Cannot reproduce Seurat.ipynb vignette; parameters not passed

[Nichal123]

Hi all,

I am trying to reproduce the Seurat.ipynb vignette to construct a reference object from a seurat object. However, I am encountering errors already from the Harmony step.
The error I get: Error in value[3L] : Invalid number of ncores provided: 0.
Maximum available cores: 64
It seems like not all parameters are passed (in the harmonymatrix function, ncores should be present, but it is not in 'utils_seurat.R'. I have tried to input the parameters that should be there (.options is missing and causing problems as well), but then Harmony is not running correctly (cell embedings, feature.loadings are all zero) Do I miss something?

Thanks in advance!

source('utils_seurat.R')

suppressPackageStartupMessages({
    library(symphony)
    library(Seurat)
    suppressWarnings({library(SeuratData)})
    library(ggplot2)
    library(dplyr)
    library(magrittr)
    library(Matrix)
    library(sctransform)
})
library(harmony)

## Install this example dataset
suppressWarnings({
    #SeuratData::InstallData('hcabm40k')
    SeuratData::LoadData('hcabm40k')    
})


cells_ref <- [email protected] %>% subset(orig.ident %in% paste0('MantonBM', 1:4)) %>% rownames()
cells_query <- [email protected] %>% subset(orig.ident %in% paste0('MantonBM', 5:8)) %>% rownames()

obj <- Seurat::CreateSeuratObject(hcabm40k@assays$RNA@counts[, cells_ref]) %>% 
    NormalizeData(normalization.method = "LogNormalize", scale.factor = 10000) %>% 
    FindVariableFeatures(selection.method = "vst", nfeatures = 2000) %>% 
    ScaleData(verbose = .verbose) %>% 
    RunPCA(verbose = .verbose) %>% 
    RunHarmony.Seurat('orig.ident', verbose = .verbose) %>% 
    FindNeighbors(dims = 1:20, reduction = 'harmony', verbose = .verbose) %>%  # previous version of this tutorial was missing reduction argument
    FindClusters(resolution = 0.5, verbose = .verbose)
#UMAP
obj[['umap']] <- RunUMAP2(Embeddings(obj, 'harmony')[, 1:20], 
                          assay='RNA', verbose=FALSE, umap.method='uwot', return.model=TRUE)
#Plot UMAP
options(repr.plot.height = 4, repr.plot.width = 6)
DimPlot(obj, reduction = 'umap', group.by = 'seurat_clusters', shuffle = TRUE)

SESSION INFO
R version 4.2.2 Patched (2022-11-10 r83330)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.6 LTS

Matrix products: default
BLAS/LAPACK: /opt/OpenBLAS/lib/libopenblasp-r0.3.13.so

locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=C LC_COLLATE=C LC_MONETARY=C LC_MESSAGES=C
[7] LC_PAPER=C LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=C LC_IDENTIFICATION=C

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

other attached packages:
[1] Matrix_1.6-4 magrittr_2.0.3 hcabm40k.SeuratData_3.0.0 SeuratData_0.2.2.9001 symphony_0.1.1
[6] patchwork_1.2.0 reshape2_1.4.4 dplyr_1.1.4 sctransform_0.4.1 aws.s3_0.3.21
[11] clustree_0.5.1 ggraph_2.1.0 ggplot2_3.4.4 harmony_1.2.0 Rcpp_1.0.12
[16] SeuratDisk_0.0.0.9021 Seurat_5.0.1 SeuratObject_5.0.1 sp_2.1-2

loaded via a namespace (and not attached):
[1] utf8_1.2.4 spatstat.explore_3.2-5 reticulate_1.34.0 tidyselect_1.2.0 htmlwidgets_1.6.4
[6] grid_4.2.2 Rtsne_0.17 devtools_2.4.5 aws.signature_0.6.0 munsell_0.5.0
[11] codetools_0.2-18 ica_1.0-3 future_1.29.0 miniUI_0.1.1.1 withr_2.5.2
[16] spatstat.random_3.2-2 colorspace_2.1-0 progressr_0.14.0 knitr_1.45 rstudioapi_0.14
[21] stats4_4.2.2 ROCR_1.0-11 SparkR_3.3.1 tensor_1.5 listenv_0.9.0
[26] MatrixGenerics_1.10.0 labeling_0.4.3 polyclip_1.10-6 bit64_4.0.5 farver_2.1.1
[31] rprojroot_2.0.4 parallelly_1.36.0 vctrs_0.6.5 generics_0.1.3 xfun_0.41
[36] R6_2.5.1 graphlayouts_1.0.2 hdf5r_1.3.8 spatstat.utils_3.0-4 cachem_1.0.8
[41] promises_1.2.1 scales_1.3.0 gtable_0.3.4 globals_0.16.2 processx_3.8.0
[46] goftest_1.2-3 spam_2.10-0 tidygraph_1.3.0 rlang_1.1.2 splines_4.2.2
[51] lazyeval_0.2.2 spatstat.geom_3.2-7 abind_1.4-5 httpuv_1.6.13 usethis_2.1.6
[56] tools_4.2.2 ellipsis_0.3.2 RColorBrewer_1.1-3 BiocGenerics_0.44.0 sessioninfo_1.2.2
[61] ggridges_0.5.5 plyr_1.8.9 base64enc_0.1-3 purrr_1.0.2 ps_1.7.2
[66] prettyunits_1.2.0 deldir_2.0-2 pbapply_1.7-2 viridis_0.6.4 cowplot_1.1.2
[71] urlchecker_1.0.1 S4Vectors_0.36.2 zoo_1.8-12 ggrepel_0.9.4 cluster_2.1.4
[76] fs_1.6.3 data.table_1.14.10 RSpectra_0.16-1 scattermore_1.2 lmtest_0.9-40
[81] RANN_2.6.1 fitdistrplus_1.1-11 matrixStats_1.2.0 pkgload_1.3.1 hms_1.1.3
[86] mime_0.12 evaluate_0.23 xtable_1.8-4 RhpcBLASctl_0.23-42 fastDummies_1.7.3
[91] IRanges_2.32.0 gridExtra_2.3 compiler_4.2.2 tibble_3.2.1 KernSmooth_2.23-20
[96] crayon_1.5.2 htmltools_0.5.7 later_1.3.2 tzdb_0.4.0 tidyr_1.3.0
[101] tweenr_2.0.2 MASS_7.3-58 rappdirs_0.3.3 readr_2.1.3 cli_3.6.2
[106] parallel_4.2.2 dotCall64_1.1-1 igraph_1.6.0 pkgconfig_2.0.3 plotly_4.10.3
[111] spatstat.sparse_3.0-3 xml2_1.3.6 stringr_1.5.1 callr_3.7.3 digest_0.6.33
[116] RcppAnnoy_0.0.21 spatstat.data_3.0-3 leiden_0.4.3.1 uwot_0.1.16 curl_5.2.0
[121] shiny_1.8.0 lifecycle_1.0.4 nlme_3.1-160 jsonlite_1.8.8 viridisLite_0.4.2
[126] fansi_1.0.6 pillar_1.9.0 lattice_0.20-45 fastmap_1.1.1 httr_1.4.7
[131] pkgbuild_1.3.1 survival_3.4-0 glue_1.6.2 remotes_2.4.2 png_0.1-8
[136] bit_4.0.5 ggforce_0.4.1 class_7.3-20 stringi_1.8.3 profvis_0.3.7
[141] RcppHNSW_0.5.0 memoise_2.0.1 irlba_2.3.5.1 future.apply_1.10.0

[Paperplane1031]

I have the same issue too, could anyone help?

[hongchengyao]

Hi @Nichal123 , thank you for using harmony! I think the Seurat.ipynb vignette you refer to is part of the seurat documentation. Could you provide a link to it so we can take a look at it?

[Nichal123]

Hi @hongchengyao, thank you for your reply. The vignette I refer to is part of the Symphony documentation
Link: https://github.com/immunogenomics/symphony/blob/main/vignettes/Seurat.ipynb.