seurat-object
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satijalab
ReadRDS and Seurat-object
I was trying to read seurat object saved previous, but was told that "Error in .requirePackage(package) : unable to find required package 'SeuratObject'".
The package "SeuratObject" is on the version 4.0.0 or higher. So is it required if I would like to read 4.0.0 objects to the environment of Seurat v3.0.0? I was frustrated that my school's HPC only have the version of 3.0.0 for Seurat. Heatbroken. Is there anyways to transfer the v4 object to v3 maybe?
Same problem here. RDS files generated with the new Seurat version cannot be read with previous versions (3.2.3 in my case). Is updating R and Seurat (along with accompanying packages) the only solution?
Loading required package: SeuratObject
Error in .requirePackage(package) :
unable to find required package ‘SeuratObject’
In addition: Warning message:
In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, :
there is no package called ‘SeuratObject’
Loading required package: SeuratObject
Error during wrapup: unable to find required package ‘SeuratObject’
Same problem here. It's the same problem with pretty much every Seurat update. I think we must definitely move away from .rds of Seurat objects. What is a good replacement? loom? h5ad? Do Loom and h5ad really contain all the seurat objects and parameters?
Also: I updated Seurat to the exact same version from which the rds file was written and that didn't help. Now I'm getting "Error: 'SCT' is not an assay" when running GetAssayData(obj) on the loaded rds object.
I solved my problem by using Seurat 4 to read the .rds file and installing the SeuratObject package. Even though the Seurat .rds objects that I received reported version 3.1.3 (sobj@version), it must have been a Seurat 4 object internally. How this can happen is a mystery to me.
I'm confused about what "SeuratObject" is and why I have to load it. I've been mystified forever how to load old Seurat2 objects when upgrading to Seurat3, but now with Seurat4 it seems even more things break. I saw this page https://satijalab.org/seurat/articles/v4_changes.html but it doesn't mention SeuratDisk or SeuratObject. So is this something not important for users?
I think there could be better documentation about how to upgrade Seurat. I have the following problems:
- I'm primarily on Seurat 4 and sometimes get Seurat 2 .rds files
- On another machine I'm on Seurat 3 and may get Seurat 4 objects (does this work?)
- Is there a way to up- or downgrade Seurat objects: 3->2, 2->3, 3<->4 ? Or are some of these compatible? How about the minor versions?
If these things are not a priority or there is another way to get objects converted, maybe through text, loom or h5Seurat files these days, that would be totally fine. I can do whatever I need to do, just right now, I have no idea where to start...
Dear all,
did anyone solve this issue? i was just trying to remake a umap plot as a test on an object i was already previously using and got the error below
DimPlot(SingleCells) Loading required package: SeuratObject Error in .requirePackage(package) : unable to find required package ‘SeuratObject’ In addition: Warning message: In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : there is no package called ‘SeuratObject’
when i tried to install seuratobject I got: install.packages("SeuratObject") Installing package into ‘/home/luna.kuleuven.be/u0096966/R/x86_64-pc-linux-gnu-library/3.6’ (as ‘lib’ is unspecified) Warning in install.packages : package ‘SeuratObject’ is not available (for R version 3.6.3)
you can find the session ifo as well below. I can unfortunately not update R on my institution's server.
Does anyone have an idea on how i can solve this?
thanks a lot
R version 3.6.3 (2020-02-29) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 20.04.2 LTS
Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0 LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages: [1] stats graphics grDevices utils datasets methods base
other attached packages: [1] Seurat_3.2.2
loaded via a namespace (and not attached):
[1] nlme_3.1-144 matrixStats_0.59.0 RcppAnnoy_0.0.18
[4] RColorBrewer_1.1-2 httr_1.4.2 sctransform_0.3.2
[7] tools_3.6.3 utf8_1.2.1 R6_2.5.0
[10] irlba_2.3.3 rpart_4.1-15 KernSmooth_2.23-16
[13] uwot_0.1.10 mgcv_1.8-31 DBI_1.1.1
[16] lazyeval_0.2.2 colorspace_2.0-1 tidyselect_1.1.1
[19] gridExtra_2.3 compiler_3.6.3 plotly_4.9.4.1
[22] scales_1.1.1 lmtest_0.9-38 spatstat.data_2.1-0
[25] ggridges_0.5.3 pbapply_1.4-3 spatstat_1.64-1
[28] goftest_1.2-2 stringr_1.4.0 digest_0.6.27
[31] spatstat.utils_2.2-0 pkgconfig_2.0.3 htmltools_0.5.1.1
[34] parallelly_1.26.0 fastmap_1.1.0 htmlwidgets_1.5.3
[37] rlang_0.4.11 shiny_1.6.0 generics_0.1.0
[40] zoo_1.8-9 jsonlite_1.7.2 ica_1.0-2
[43] dplyr_1.0.7 magrittr_2.0.1 patchwork_1.1.1
[46] Matrix_1.2-18 Rcpp_1.0.6 munsell_0.5.0
[49] fansi_0.5.0 abind_1.4-5 reticulate_1.20
[52] lifecycle_1.0.0 stringi_1.6.2 MASS_7.3-51.5
[55] Rtsne_0.15 plyr_1.8.6 grid_3.6.3
[58] parallel_3.6.3 listenv_0.8.0 promises_1.2.0.1
[61] ggrepel_0.9.1 crayon_1.4.1 miniUI_0.1.1.1
[64] deldir_0.2-10 lattice_0.20-40 cowplot_1.1.1
[67] splines_3.6.3 tensor_1.5 pillar_1.6.1
[70] igraph_1.2.6 future.apply_1.7.0 reshape2_1.4.4
[73] codetools_0.2-16 leiden_0.3.8 glue_1.4.2
[76] data.table_1.14.0 png_0.1-7 vctrs_0.3.8
[79] httpuv_1.6.1 gtable_0.3.0 RANN_2.6.1
[82] purrr_0.3.4 polyclip_1.10-0 tidyr_1.1.3
[85] future_1.21.0 assertthat_0.2.1 ggplot2_3.3.4
[88] rsvd_1.0.3 mime_0.10 xtable_1.8-4
[91] later_1.2.0 survival_3.1-8 viridisLite_0.4.0
[94] tibble_3.1.2 cluster_2.1.0 globals_0.14.0
[97] fitdistrplus_1.1-5 ellipsis_0.3.2 ROCR_1.0-11
fyi: my object was created with seurat 3.2.3. so this is a mystery to me
Yes, this is why I was so surprised by the error: I saved the object on a server which doesn't have SeuratObject installed (at least not to my knowledge) and on a Seurat3 version.
On Tue, Jun 22, 2021 at 1:50 PM SaraVerbandt @.***> wrote:
fyi: my object was created with seurat 3.2.3. so this is a mystery to me
— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/mojaveazure/seurat-object/issues/14#issuecomment-865915941, or unsubscribe https://github.com/notifications/unsubscribe-auth/AACL4TPYJZ66RTGNG6NK5EDTUB2IPANCNFSM44X7NSSQ .
I simply copied the object to my laptop, installed SeuratObject there, and am working there for now. But Seurat .rds files have become a bit of a de-facto standard and you can even find them in GEO, so it's really important to be able to load them.
On Tue, Jun 22, 2021 at 2:07 PM SaraVerbandt @.***> wrote:
same here let's hope someone can help us
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thanks yes indeed, i did the same this morning. however, my file is very big so i am wondering how to then get it working on the server again. do you have a suggestion for that by any chance? thanks a million
No sorry, that's the thing I'm also wondering about. Maybe, if the seurat developers don't have time to reply, you could post this question on Biostars?
On Tue, Jun 22, 2021 at 2:38 PM SaraVerbandt @.***> wrote:
thanks yes indeed, i did the same this morning. however, my file is very big so i am wondering how to then get it working on the server again. do you have a suggestion for that by any chance? thanks a million
— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/mojaveazure/seurat-object/issues/14#issuecomment-865946797, or unsubscribe https://github.com/notifications/unsubscribe-auth/AACL4TK4FVELB3WIM3EPT33TUB73RANCNFSM44X7NSSQ .
Hi,
I've encountered the same issue, where an object shared with me was produced with Seurat V4, but I needed to work with it in in Seurat V3. In my case, the analysis I needed to do in Seurat V3 was not extensive, so I re-constructed the Seurat object in V3 using the components from V4, and then re-did a bit of the processing (e.g. normalization) as a very roundabout way to get the data. It's a temporary workaround and of course, this would only work if you have access to both versions of Seurat, e.g. in different R library paths.
This function would be run with Seurat V4:
library(magrittr)
library(Seurat)
#' Given a Seurat object which requires the SeuratObject package
#' extract the necessary info to be able to re-create the object
#' in Seurat V3
#'
#' @param seurat Seurat object
#' @param out Character, path to .Rda file where output should be saved, e.g. "sample.seurat_components.Rda"
extract_seurat_v4 <- function(seurat, out, project.name = NULL) {
message("@ Seurat version is ", packageVersion("Seurat"))
message("@ extracting data...")
# get raw counts
counts <- GetAssayData(seurat, "counts")
# get dim reductions
seurat <- AddMetaData(seurat,
metadata = seurat@[email protected], col.name = c("UMAP_1", "UMAP_2"))
seurat <- AddMetaData(seurat,
metadata = seurat@[email protected], col.name = c("PC_1", "PC_2"))
# get active ident
seurat[["active.ident"]] <- Idents(object = seurat)
# extract metadata
meta <- [email protected]
# get commands record
commands <- seurat@commands
# assign a project name
if (is.null(project.name)) project.name <- [email protected]
message("@ saving data...")
save(counts, meta, commands, project.name, file = out)
message("@ done. Components written to ", out)
}
This function be run with Seurat V3, and would load up the output of the previous function:
library(magrittr)
library(Seurat)
#' Given the components of a Seurat object, create a Seurat V3 object
#'
#' @param components_path Character, path to .Rda file where components are saved
create_seurat_v3 <- function(components_path) {
message("@ Seurat version is ", packageVersion("Seurat"))
message("@ loading components...")
load(components_path)
message("@ populating seurat object...")
# get project name from file name
project.name <- gsub(".seurat_components.Rda$", "", basename(components_path))
# create the object
seurat <- CreateSeuratObject(
counts = counts,
meta.data = meta,
project.name = project.name)
# populate dimensionality reduction
seurat@reductions$pca <- CreateDimReducObject(embeddings = as.matrix(meta[, c("PC_1", "PC_2")]))
seurat@reductions$umap <- CreateDimReducObject(embeddings = as.matrix(meta[, c("UMAP_1", "UMAP_2")]))
# set active ident
Idents(seurat) <- "active.ident"
# save original commands
seurat@misc$commands_original <- commands
# clean up meta
seurat$active.ident <- NULL
seurat$UMAP_1 <- NULL
seurat$UMAP_2 <- NULL
seurat$PC_1 <- NULL
seurat$PC_2 <- NULL
# log-normalize, find HVG, scale data
message("@ normalizing & scaling data...")
seurat <- seurat %>%
NormalizeData(normalization.method = "LogNormalize",
scale.factor = 10000) %>%
# identify variable genes
FindVariableFeatures(mean.function = ExpMean,
dispersion.function = LogVMR) %>%
# regress out variables which are sources of unwanted variation, and z-score data
ScaleData(vars.to.regress = "nCount_RNA")
message("@ done.")
return(seurat)
}
Hi all, sorry for the delay
The reason Seurat objects in v4 cannot be read in v3 is that in v4 the class definition was moved into {SeuratObject}. S4 classes (like Seurat) are tied to their package environment, unlike S3 classes which are tied to their name. As such, all Seurat objects created in v4 are tied to the {SeuratObject} package, not the {Seurat} package. To get around this, you can install Seurat v3 and SeuratObject v4 on the same machine (one that has R >= 4.0) installed. Then, use SeuratObject:::UpdateClassPkg to move a v4 Seurat object from the {SeuratObject} environment to the v3 {Seurat} environment
library(Seurat) # Make sure v3 {Seurat} is attached
v3_obj <- SeuratObject:::UpdateClassPkg(v4_obj, from = "SeuratObject", to = "Seurat")
This will not work if {Seurat} v3 is not installed and attached. Unfortunately, this means that you'll have to uninstall {Seurat} v4 from your machine and reinstall v3
If it's not feasible to remove {Seurat} v4 and reinstall v3, I would be happy build and provide a Docker image that has {Seurat} v3 and {SeuratObject} v4 to provide an isolated environment to run conversion
Hello @mojaveazure, I just tried your approach to convert v4 to v3, but met an error. Could you help to fix it? Thanks. Kun
WTGCv3 <- SeuratObject:::UpdateClassPkg(WTGC, from = "SeuratObject", to = "Seurat") Error in initialize(value, ...) : invalid name for slot of class “Seurat”: images In addition: Warning message: package ‘SeuratObject’ was built under R version 4.1.2
sessionInfo() R version 4.1.1 (2021-08-10) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 19043)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C LC_TIME=English_United States.1252
system code page: 936
attached base packages: [1] stats graphics grDevices utils datasets methods base
other attached packages: [1] SeuratObject_4.0.4 Seurat_3.1.5
loaded via a namespace (and not attached):
[1] httr_1.4.2 tidyr_1.1.4 jsonlite_1.7.2 viridisLite_0.4.0 splines_4.1.1
[6] leiden_0.3.9 assertthat_0.2.1 BiocManager_1.30.16 ggrepel_0.9.1 globals_0.14.0
[11] pillar_1.6.4 lattice_0.20-45 glue_1.5.0 reticulate_1.22 digest_0.6.28
[16] RColorBrewer_1.1-2 colorspace_2.0-2 cowplot_1.1.1 htmltools_0.5.2 Matrix_1.3-4
[21] plyr_1.8.6 pkgconfig_2.0.3 tsne_0.1-3 listenv_0.8.0 purrr_0.3.4
[26] patchwork_1.1.1 scales_1.1.1 RANN_2.6.1 Rtsne_0.15 tibble_3.1.6
[31] generics_0.1.1 ggplot2_3.3.5 ellipsis_0.3.2 ROCR_1.0-11 pbapply_1.5-0
[36] lazyeval_0.2.2 survival_3.2-13 magrittr_2.0.1 crayon_1.4.2 future_1.23.0
[41] fansi_0.5.0 parallelly_1.29.0 nlme_3.1-153 MASS_7.3-54 ica_1.0-2
[46] tools_4.1.1 fitdistrplus_1.1-6 data.table_1.14.2 lifecycle_1.0.1 matrixStats_0.61.0
[51] stringr_1.4.0 plotly_4.10.0 munsell_0.5.0 cluster_2.1.2 irlba_2.3.3
[56] compiler_4.1.1 rsvd_1.0.5 rlang_0.4.12 grid_4.1.1 ggridges_0.5.3
[61] RcppAnnoy_0.0.19 htmlwidgets_1.5.4 igraph_1.2.9 gtable_0.3.0 codetools_0.2-18
[66] DBI_1.1.1 reshape2_1.4.4 R6_2.5.1 gridExtra_2.3 zoo_1.8-9
[71] dplyr_1.0.7 uwot_0.1.10 fastmap_1.1.0 future.apply_1.8.1 utf8_1.2.2
[76] KernSmooth_2.23-20 ape_5.5 stringi_1.7.6 parallel_4.1.1 Rcpp_1.0.7
[81] vctrs_0.3.8 sctransform_0.3.2 png_0.1-7 tidyselect_1.1.1 lmtest_0.9-39
@kunUCSD Hello Kun,
I also tried and got the same error as you did. Could you please explain what you did to fix it ?
Or Maybe @mojaveazure you also have the solution ?
Thanks both of you
For people who have the same problem and cannot be solved by the posts above, I found a way to work around it. In R 4.1, use SeuratV4 to transform the Seurat object to SCE object. Then in R 3.6, read in the SCE object and use SeuratV3 to transform back to Seurat object. Then you should be good to go.
Hi @JasonOSS, Sorry, I missed your message... I used the same approach as ruiye88 mentioned. Best, K
Hi All,
My 2 cents after trying out converting via SingleCellExperiment object; SingleCellExperiment doesn't preserve all the info in the Seurat Object. For eg:- Standard deviations on the PCA embeddings. (Not too big an issue, but could hinder your pipelines) and other smaller issues such as PCA reduction is saved as "PCA" instead of "pca" etc.
Converting through H5Seurat seemed much better as it is particularly made for Seurat Object and seemed to preserve most features (as far as I have checked); @mojaveazure will have a better say on this.
Load Seurat in v4 environment and save it in SeuratH5 format.
SaveH5Seurat(MySeuratObject, "SO.H5Seurat")
Load seurat object into Seurat_v3 environment from the H5Seurat format
MySeuObject <- LoadH5Seurat("SO.H5Seurat")
Another note:-
If you rely on conda environments, an environment with the following installation worked seemlessly (had conflicts when I geared up for advanced versions)
conda create -n newenv
conda activate newenv
conda install -c conda-forge r-seuratdisk=4.0.4=r40h03ef668_0
conda install -c bioconda bioconductor-glmgampoi=1.2.0=r40h399db7b_1
conda install -c conda-forge r-harmony=0.1=r40h7d875b9_1
Full list of packages (the dependencies that got installed) with versions:-
# Name Version Build Channel
_libgcc_mutex 0.1 conda_forge conda-forge
_openmp_mutex 4.5 1_gnu conda-forge
_r-mutex 1.0.1 anacondar_1 conda-forge
binutils_impl_linux-64 2.36.1 h193b22a_2 conda-forge
binutils_linux-64 2.36 hf3e587d_9 conda-forge
bioconductor-beachmat 2.6.4 r40h399db7b_1 bioconda
bioconductor-biobase 2.50.0 r40hd029910_1 bioconda
bioconductor-biocgenerics 0.36.0 r40hdfd78af_1 bioconda
bioconductor-biocparallel 1.24.1 r40h399db7b_0 bioconda
bioconductor-delayedarray 0.16.3 r40hd029910_0 bioconda
bioconductor-delayedmatrixstats 1.12.3 r40hdfd78af_0 bioconda
bioconductor-genomeinfodb 1.26.4 r40hdfd78af_0 bioconda
bioconductor-genomeinfodbdata 1.2.4 r40hdfd78af_2 bioconda
bioconductor-genomicranges 1.42.0 r40hd029910_1 bioconda
bioconductor-glmgampoi 1.2.0 r40h399db7b_1 bioconda
bioconductor-hdf5array 1.18.1 r40hd029910_0 bioconda
bioconductor-iranges 2.24.1 r40hd029910_0 bioconda
bioconductor-matrixgenerics 1.2.1 r40hdfd78af_0 bioconda
bioconductor-rhdf5 2.34.0 r40h399db7b_1 bioconda
bioconductor-rhdf5filters 1.2.0 r40h399db7b_1 bioconda
bioconductor-rhdf5lib 1.12.1 r40hd029910_0 bioconda
bioconductor-s4vectors 0.28.1 r40hd029910_0 bioconda
bioconductor-singlecellexperiment 1.12.0 r40hdfd78af_1 bioconda
bioconductor-sparsematrixstats 1.2.1 r40h399db7b_0 bioconda
bioconductor-summarizedexperiment 1.20.0 r40hdfd78af_1 bioconda
bioconductor-xvector 0.30.0 r40hd029910_1 bioconda
bioconductor-zlibbioc 1.36.0 r40hd029910_1 bioconda
bwidget 1.9.14 ha770c72_1 conda-forge
bzip2 1.0.8 h7f98852_4 conda-forge
c-ares 1.18.1 h7f98852_0 conda-forge
ca-certificates 2022.3.29 h06a4308_0
cairo 1.16.0 hf32fb01_1
curl 7.82.0 h2283fc2_0 conda-forge
expat 2.4.8 h27087fc_0 conda-forge
font-ttf-dejavu-sans-mono 2.37 hab24e00_0 conda-forge
font-ttf-inconsolata 3.000 h77eed37_0 conda-forge
font-ttf-source-code-pro 2.038 h77eed37_0 conda-forge
font-ttf-ubuntu 0.83 hab24e00_0 conda-forge
fontconfig 2.14.0 h8e229c2_0 conda-forge
fonts-conda-ecosystem 1 0 conda-forge
fonts-conda-forge 1 0 conda-forge
freetype 2.11.0 h70c0345_0
fribidi 1.0.10 h36c2ea0_0 conda-forge
gcc_impl_linux-64 10.3.0 hf2f2afa_14 conda-forge
gcc_linux-64 10.3.0 hc39de41_9 conda-forge
gettext 0.21.0 hf68c758_0
gfortran_impl_linux-64 10.3.0 h73f4979_14 conda-forge
gfortran_linux-64 10.3.0 hb09a455_9 conda-forge
glib 2.70.2 h780b84a_4 conda-forge
glib-tools 2.70.2 h780b84a_4 conda-forge
gmp 6.2.1 h58526e2_0 conda-forge
graphite2 1.3.14 h23475e2_0
gsl 2.7.1 hd82f3ee_0
gxx_impl_linux-64 10.3.0 hf2f2afa_14 conda-forge
gxx_linux-64 10.3.0 h2593f52_9 conda-forge
harfbuzz 4.2.0 hf9f4e7c_1 conda-forge
hdf5 1.12.1 nompi_h4df4325_104 conda-forge
icu 70.1 h27087fc_0 conda-forge
jbig 2.1 h7f98852_2003 conda-forge
jpeg 9e h7f98852_0 conda-forge
kernel-headers_linux-64 2.6.32 he073ed8_15 conda-forge
keyutils 1.6.1 h166bdaf_0 conda-forge
krb5 1.19.3 h08a2579_0 conda-forge
ld_impl_linux-64 2.36.1 hea4e1c9_2 conda-forge
lerc 3.0 h9c3ff4c_0 conda-forge
libblas 3.9.0 14_linux64_openblas conda-forge
libcurl 7.82.0 h2283fc2_0 conda-forge
libdeflate 1.10 h7f98852_0 conda-forge
libedit 3.1.20210910 h7f8727e_0
libev 4.33 h516909a_1 conda-forge
libffi 3.4.2 h7f98852_5 conda-forge
libgcc-devel_linux-64 10.3.0 he6cfe16_14 conda-forge
libgcc-ng 11.2.0 h1d223b6_14 conda-forge
libgfortran-ng 11.2.0 h69a702a_14 conda-forge
libgfortran5 11.2.0 h5c6108e_14 conda-forge
libglib 2.70.2 h174f98d_4 conda-forge
libgomp 11.2.0 h1d223b6_14 conda-forge
libiconv 1.16 h516909a_0 conda-forge
liblapack 3.9.0 14_linux64_openblas conda-forge
libnghttp2 1.47.0 he49606f_0 conda-forge
libnsl 2.0.0 h7f98852_0 conda-forge
libopenblas 0.3.20 pthreads_h78a6416_0 conda-forge
libpng 1.6.37 h21135ba_2 conda-forge
libsanitizer 10.3.0 h26c7422_14 conda-forge
libssh2 1.10.0 ha35d2d1_2 conda-forge
libstdcxx-devel_linux-64 10.3.0 he6cfe16_14 conda-forge
libstdcxx-ng 11.2.0 he4da1e4_14 conda-forge
libtiff 4.3.0 h542a066_3 conda-forge
libuuid 2.32.1 h7f98852_1000 conda-forge
libwebp-base 1.2.2 h7f98852_1 conda-forge
libxcb 1.14 h7b6447c_0
libxml2 2.9.12 h22db469_2 conda-forge
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r-rcolorbrewer 1.1_3 r40h785f33e_0 conda-forge
r-rcpp 1.0.8.3 r40h7525677_0 conda-forge
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readline 8.1.2 h7f8727e_1
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setuptools 62.0.0 pypi_0 pypi
sqlite 3.38.2 hc218d9a_0
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tk 8.6.12 h27826a3_0 conda-forge
tktable 2.10 hb7b940f_3 conda-forge
tzdata 2022a h191b570_0 conda-forge
wheel 0.37.1 pyhd8ed1ab_0 conda-forge
xorg-kbproto 1.0.7 h7f98852_1002 conda-forge
xorg-libice 1.0.10 h7f98852_0 conda-forge
xorg-libsm 1.2.3 hd9c2040_1000 conda-forge
xorg-libx11 1.7.2 h7f98852_0 conda-forge
xorg-libxt 1.2.1 h7f98852_2 conda-forge
xorg-xproto 7.0.31 h7f98852_1007 conda-forge
xz 5.2.5 h516909a_1 conda-forge
zlib 1.2.11 h166bdaf_1014 conda-forge
zstd 1.5.2 ha95c52a_0 conda-forge
Hi @maximilianh, did you end up using any of these workarounds? I am interested in wrangling something for the GB but I'm encountering this issue.
For anyone interested, there's an image on Docker Hub that has the Seurat V4 library installed, and I'm able to load it. The image is here: https://hub.docker.com/r/jafoltz/seuratv4.1withdsb
$ docker run -it jafoltz/seuratv4.1withdsb
R version 4.1.0 (2021-05-18) -- "Camp Pontanezen"
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.
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.
> library("Seurat")
Attaching SeuratObject
>
