Open kguion1 opened 2 years ago
RubD
commented
2 years ago Hi @kguion1
Thanks for bringing this to our attention. We will take a look and follow up shortly.
We will likely first provide a working example of this tutorial (that you can run) to ensure that there are not compatibility issues. If that doesn't resolve the issue we will need to dig further.
kguion1
commented
2 years ago Hi, I was curious if there was an update on this? I do not see the issues page anymore on github.
Best, Kate
On Sun, Sep 25, 2022 at 5:15 PM Ruben Dries @.***> wrote:
Thanks for bringing this to our attention. We will take a look and follow up shortly.
We will likely first provide a working example of this tutorial (that you can run) to ensure that there are not compatibility issues. If that doesn't resolve the issue we will need to dig further.
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Hi, excited to start using this package! I am trying to covert a seurat object to a giotto object for an analysis of pre-processed visium data. I tried using the
seuratToGiotto()function and received this error:Error in Giotto::seuratToGiotto(spatial_5c, spatial_assay = "SCT", : trying to get slot "data" from an object of a basic class ("NULL") with no slotsI looked at my seurat object and in assay "SCT" there is an data slot, so I am not sure why it is not finding it?
Any help would be greatly appreciated!
I am using Giotto version 2.0.0.998
g = Giotto::seuratToGiotto(spatial_5c, spatial_assay="SCT", dim_reduction = c("pca", "umap"))Error in Giotto::seuratToGiotto(spatial_5c, spatial_assay = "SCT", dim_reduction = c("pca", : trying to get slot "data" from an object of a basic class ("NULL") with no slots> str(spatial_5c@assays$SCT)Formal class 'SCTAssay' [package "Seurat"] with 9 slots ..@ SCTModel.list:List of 1 .. ..$ model1:Formal class 'SCTModel' [package "Seurat"] with 7 slots .. .. .. ..@ feature.attributes:'data.frame': 18065 obs. of 12 variables: .. .. .. .. ..$ detection_rate : num [1:18065] 0.0091 0.0148 0.0313 0.1706 0.0233 ... .. .. .. .. ..$ gmean : num [1:18065] 0.00632 0.0103 0.02191 0.13857 0.01652 ... .. .. .. .. ..$ variance : num [1:18065] 0.00902 0.01457 0.03031 0.22125 0.02446 ... .. .. .. .. ..$ residual_mean : num [1:18065] 0.00304 0.0025 0.01036 0.00576 0.01154 ... .. .. .. .. ..$ residual_variance : num [1:18065] 0.976 0.953 0.965 1.015 1.052 ... .. .. .. .. ..$ theta : num [1:18065] 0.287 0.285 0.507 2.689 0.387 ... .. .. .. .. ..$ (Intercept) : num [1:18065] -8.14 -6.65 -6.03 -6.92 -5.92 ... .. .. .. .. ..$ log_umi : num [1:18065] 0.786 0.559 0.579 1.222 0.489 ... .. .. .. .. ..$ genes_log_gmean_step1: int [1:18065] 0 0 0 1 0 0 0 0 0 0 ... .. .. .. .. ..$ step1theta : num [1:18065] NA NA NA 2.04 NA ... .. .. .. .. ..$ step1(Intercept) : num [1:18065] NA NA NA -7.5 NA ... .. .. .. .. ..$ step1_log_umi : num [1:18065] NA NA NA 1.36 NA ... .. .. .. ..@ cell.attributes :'data.frame': 1759 obs. of 3 variables: .. .. .. .. ..$ umi : num [1:1759] 29295 28600 39127 23710 35203 ... .. .. .. .. ..$ log_umi : num [1:1759] 4.47 4.46 4.59 4.37 4.55 ... .. .. .. .. ..$ cells_step1: int [1:1759] 1 1 1 1 1 1 1 1 1 1 ... .. .. .. ..@ clips :List of 2 .. .. .. .. ..$ sct: num [1:2] -7.66 7.66 .. .. .. .. ..$ vst: num [1:2] -41.9 41.9 .. .. .. ..@ umi.assay : chr "spatial" .. .. .. ..@ model : chr "y ~ log_umi" .. .. .. ..@ arguments :List of 26 .. .. .. .. ..$ latent_var : chr "log_umi" .. .. .. .. ..$ n_genes : num 2000 .. .. .. .. ..$ n_cells : num 1759 .. .. .. .. ..$ method : chr "poisson" .. .. .. .. ..$ do_regularize : logi TRUE .. .. .. .. ..$ theta_regularization : chr "od_factor" .. .. .. .. ..$ res_clip_range : num [1:2] -41.9 41.9 .. .. .. .. ..$ bin_size : num 500 .. .. .. .. ..$ min_cells : num 5 .. .. .. .. ..$ residual_type : chr "pearson" .. .. .. .. ..$ return_cell_attr : logi TRUE .. .. .. .. ..$ return_gene_attr : logi TRUE .. .. .. .. ..$ return_corrected_umi : logi TRUE .. .. .. .. ..$ min_variance : num -Inf .. .. .. .. ..$ bw_adjust : num 3 .. .. .. .. ..$ gmean_eps : num 1 .. .. .. .. ..$ theta_estimation_fun : chr "theta.ml" .. .. .. .. ..$ exclude_poisson : logi FALSE .. .. .. .. ..$ use_geometric_mean : logi TRUE .. .. .. .. ..$ use_geometric_mean_offset: logi FALSE .. .. .. .. ..$ fix_intercept : logi FALSE .. .. .. .. ..$ fix_slope : logi FALSE .. .. .. .. ..$ scale_factor : logi NA .. .. .. .. ..$ verbosity : num 0 .. .. .. .. ..$ sct.clip.range : num [1:2] -7.66 7.66 .. .. .. .. ..$ sct.method : chr "default" .. .. .. ..@ medianumi : num 23806 ..@ counts :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots .. .. ..@ i : int [1:8246426] 3 7 8 14 15 20 23 27 30 32 ... .. .. ..@ p : int [1:1760] 0 5024 9823 15237 19704 25187 28902 33782 39814 43372 ... .. .. ..@ Dim : int [1:2] 18065 1759 .. .. ..@ Dimnames:List of 2 .. .. .. ..$ : chr [1:18065] "AL627309.1" "AL627309.5" "LINC01409" "LINC01128" ... .. .. .. ..$ : chr [1:1759] "AAACCGGGTAGGTACC.1" "AAACCGTTCGTCCAGG.1" "AAACGAGACGGTTGAT.1" "AAACTGCTGGCTCCAA.1" ... .. .. ..@ x : num [1:8246426] 1 1 1 1 1 2 1 1 2 1 ... .. .. ..@ factors : list() ..@ data :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots .. .. ..@ i : int [1:8246426] 3 7 8 14 15 20 23 27 30 32 ... .. .. ..@ p : int [1:1760] 0 5024 9823 15237 19704 25187 28902 33782 39814 43372 ... .. .. ..@ Dim : int [1:2] 18065 1759 .. .. ..@ Dimnames:List of 2 .. .. .. ..$ : chr [1:18065] "AL627309.1" "AL627309.5" "LINC01409" "LINC01128" ... .. .. .. ..$ : chr [1:1759] "AAACCGGGTAGGTACC.1" "AAACCGTTCGTCCAGG.1" "AAACGAGACGGTTGAT.1" "AAACTGCTGGCTCCAA.1" ... .. .. ..@ x : num [1:8246426] 0.693 0.693 0.693 0.693 0.693 ... .. .. ..@ factors : list() ..@ scale.data : num [1:3000, 1:1759] -0.049 -0.04 -0.833 -0.085 -0.16 ... .. ..- attr(*, "dimnames")=List of 2 .. .. ..$ : chr [1:3000] "FAM41C" "PERM1" "HES4" "AL390719.2" ... .. .. ..$ : chr [1:1759] "AAACCGGGTAGGTACC.1" "AAACCGTTCGTCCAGG.1" "AAACGAGACGGTTGAT.1" "AAACTGCTGGCTCCAA.1" ... ..@ key : chr "sct" ..@ assay.orig : NULL ..@ var.features : chr [1:3000] "IGKC" "IGHA1" "IGHG3" "IGLC2" ... ..@ meta.features:'data.frame': 18065 obs. of 0 variables ..@ misc : Named list()