Entering edit mode
3.1 years ago
akh22
▴
110
Hi,
I have a following Seurat obj ;
> str(pbmc10k@assays)
List of 4
$ RNA :Formal class 'Assay' [package "Seurat"] with 8 slots
.. ..@ counts :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
.. .. .. ..@ i : int [1:24330253] 25 30 32 42 43 44 51 59 60 62 ...
.. .. .. ..@ p : int [1:10195] 0 4803 7036 11360 11703 15846 18178 20413 22584 27802 ...
.. .. .. ..@ Dim : int [1:2] 36601 10194
.. .. .. ..@ Dimnames:List of 2
.. .. .. .. ..$ : chr [1:36601] "MIR1302-2HG" "FAM138A" "OR4F5" "AL627309.1" ...
.. .. .. .. ..$ : chr [1:10194] "AAACCCACATAACTCG-1" "AAACCCACATGTAACC-1" "AAACCCAGTGAGTCAG-1" "AAACCCAGTGCTTATG-1" ...
.. .. .. ..@ x : num [1:24330253] 1 2 1 1 1 3 1 1 1 1 ...
.. .. .. ..@ factors : list()
.. ..@ data :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
.. .. .. ..@ i : int [1:24330253] 25 30 32 42 43 44 51 59 60 62 ...
.. .. .. ..@ p : int [1:10195] 0 4803 7036 11360 11703 15846 18178 20413 22584 27802 ...
.. .. .. ..@ Dim : int [1:2] 36601 10194
.. .. .. ..@ Dimnames:List of 2
.. .. .. .. ..$ : chr [1:36601] "MIR1302-2HG" "FAM138A" "OR4F5" "AL627309.1" ...
.. .. .. .. ..$ : chr [1:10194] "AAACCCACATAACTCG-1" "AAACCCACATGTAACC-1" "AAACCCAGTGAGTCAG-1" "AAACCCAGTGCTTATG-1" ...
.. .. .. ..@ x : num [1:24330253] 0.367 0.634 0.367 0.367 0.367 ...
.. .. .. ..@ factors : list()
.. ..@ scale.data : num [1:2000, 1:10194] -0.0829 -0.2648 -0.195 -0.0133 1.2823 ...
.. .. ..- attr(*, "dimnames")=List of 2
.. .. .. ..$ : chr [1:2000] "PLEKHN1" "HES4" "ISG15" "LINC01342" ...
.. .. .. ..$ : chr [1:10194] "AAACCCACATAACTCG-1" "AAACCCACATGTAACC-1" "AAACCCAGTGAGTCAG-1" "AAACCCAGTGCTTATG-1" ...
.. ..@ key : chr "rna_"
.. ..@ assay.orig : NULL
.. ..@ var.features : chr [1:2000] "PTGDS" "IGLC3" "PPBP" "CXCL10" ...
.. ..@ meta.features:'data.frame': 36601 obs. of 5 variables:
.. .. ..$ vst.mean : num [1:36601] 0 0 0 0.00392 0 ...
.. .. ..$ vst.variance : num [1:36601] 0 0 0 0.00391 0 ...
.. .. ..$ vst.variance.expected : num [1:36601] 0 0 0 0.00452 0 ...
.. .. ..$ vst.variance.standardized: num [1:36601] 0 0 0 0.865 0 ...
.. .. ..$ vst.variable : logi [1:36601] FALSE FALSE FALSE FALSE FALSE FALSE ...
.. ..@ misc : NULL
$ unspliced:Formal class 'Assay' [package "Seurat"] with 8 slots
.. ..@ counts :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
.. .. .. ..@ i : int [1:20057627] 8 46 53 69 70 71 72 73 84 89 ...
.. .. .. ..@ p : int [1:10195] 0 3837 6398 9489 10407 14220 16595 18856 20831 24609 ...
.. .. .. ..@ Dim : int [1:2] 36601 10194
.. .. .. ..@ Dimnames:List of 2
.. .. .. .. ..$ : chr [1:36601] "BX004987.1" "AC145212.1" "MAFIP" "AC011043.1" ...
.. .. .. .. ..$ : chr [1:10194] "AAACCCACATAACTCG-1" "AAACCCACATGTAACC-1" "AAACCCAGTGAGTCAG-1" "AAACCCAGTGCTTATG-1" ...
.. .. .. ..@ x : num [1:20057627] 1 3 1 1 2 1 1 9 1 1 ...
.. .. .. ..@ factors : list()
.. ..@ data :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
.. .. .. ..@ i : int [1:20057627] 8 46 53 69 70 71 72 73 84 89 ...
.. .. .. ..@ p : int [1:10195] 0 3837 6398 9489 10407 14220 16595 18856 20831 24609 ...
.. .. .. ..@ Dim : int [1:2] 36601 10194
.. .. .. ..@ Dimnames:List of 2
.. .. .. .. ..$ : chr [1:36601] "BX004987.1" "AC145212.1" "MAFIP" "AC011043.1" ...
.. .. .. .. ..$ : chr [1:10194] "AAACCCACATAACTCG-1" "AAACCCACATGTAACC-1" "AAACCCAGTGAGTCAG-1" "AAACCCAGTGCTTATG-1" ...
.. .. .. ..@ x : num [1:20057627] 1 3 1 1 2 1 1 9 1 1 ...
.. .. .. ..@ factors : list()
.. ..@ scale.data : num[0 , 0 ]
.. ..@ key : chr "unspliced_"
.. ..@ assay.orig : NULL
.. ..@ var.features : logi(0)
.. ..@ meta.features:'data.frame': 36601 obs. of 0 variables
.. ..@ misc : NULL
$ spliced :Formal class 'Assay' [package "Seurat"] with 8 slots
.. ..@ counts :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
.. .. .. ..@ i : int [1:19059316] 48 49 50 54 59 60 61 65 70 72 ...
.. .. .. ..@ p : int [1:10195] 0 3840 5465 8968 9150 12398 14145 15854 17504 21746 ...
.. .. .. ..@ Dim : int [1:2] 36601 10194
.. .. .. ..@ Dimnames:List of 2
.. .. .. .. ..$ : chr [1:36601] "BX004987.1" "AC145212.1" "MAFIP" "AC011043.1" ...
.. .. .. .. ..$ : chr [1:10194] "AAACCCACATAACTCG-1" "AAACCCACATGTAACC-1" "AAACCCAGTGAGTCAG-1" "AAACCCAGTGCTTATG-1" ...
.. .. .. ..@ x : num [1:19059316] 1 1 3 1 1 1 1 1 1 2 ...
.. .. .. ..@ factors : list()
.. ..@ data :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
.. .. .. ..@ i : int [1:19059316] 48 49 50 54 59 60 61 65 70 72 ...
.. .. .. ..@ p : int [1:10195] 0 3840 5465 8968 9150 12398 14145 15854 17504 21746 ...
.. .. .. ..@ Dim : int [1:2] 36601 10194
.. .. .. ..@ Dimnames:List of 2
.. .. .. .. ..$ : chr [1:36601] "BX004987.1" "AC145212.1" "MAFIP" "AC011043.1" ...
.. .. .. .. ..$ : chr [1:10194] "AAACCCACATAACTCG-1" "AAACCCACATGTAACC-1" "AAACCCAGTGAGTCAG-1" "AAACCCAGTGCTTATG-1" ...
.. .. .. ..@ x : num [1:19059316] 1 1 3 1 1 1 1 1 1 2 ...
.. .. .. ..@ factors : list()
.. ..@ scale.data : num[0 , 0 ]
.. ..@ key : chr "spliced_"
.. ..@ assay.orig : NULL
.. ..@ var.features : logi(0)
.. ..@ meta.features:'data.frame': 36601 obs. of 0 variables
.. ..@ misc : NULL
$ SCT :Formal class 'Assay' [package "Seurat"] with 8 slots
.. ..@ counts :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
.. .. .. ..@ i : int [1:22836556] 12 17 21 22 23 45 59 60 74 79 ...
.. .. .. ..@ p : int [1:10195] 0 2675 4907 7438 8739 12423 14750 16985 19156 21564 ...
.. .. .. ..@ Dim : int [1:2] 20666 10194
.. .. .. ..@ Dimnames:List of 2
.. .. .. .. ..$ : chr [1:20666] "AL627309.1" "AL627309.5" "AL627309.4" "AL669831.2" ...
.. .. .. .. ..$ : chr [1:10194] "AAACCCACATAACTCG-1" "AAACCCACATGTAACC-1" "AAACCCAGTGAGTCAG-1" "AAACCCAGTGCTTATG-1" ...
.. .. .. ..@ x : num [1:22836556] 1 1 1 1 1 1 1 2 1 1 ...
.. .. .. ..@ factors : list()
.. ..@ data :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
.. .. .. ..@ i : int [1:22836556] 12 17 21 22 23 45 59 60 74 79 ...
.. .. .. ..@ p : int [1:10195] 0 2675 4907 7438 8739 12423 14750 16985 19156 21564 ...
.. .. .. ..@ Dim : int [1:2] 20666 10194
.. .. .. ..@ Dimnames:List of 2
.. .. .. .. ..$ : chr [1:20666] "AL627309.1" "AL627309.5" "AL627309.4" "AL669831.2" ...
.. .. .. .. ..$ : chr [1:10194] "AAACCCACATAACTCG-1" "AAACCCACATGTAACC-1" "AAACCCAGTGAGTCAG-1" "AAACCCAGTGCTTATG-1" ...
.. .. .. ..@ x : num [1:22836556] 0.693 0.693 0.693 0.693 0.693 ...
.. .. .. ..@ factors : list()
.. ..@ scale.data : num [1:3000, 1:10194] -0.1333 -0.5897 -1.0906 -0.0483 -0.0499 ...
.. .. ..- attr(*, "dimnames")=List of 2
.. .. .. ..$ : chr [1:3000] "PLEKHN1" "HES4" "ISG15" "AL390719.3" ...
.. .. .. ..$ : chr [1:10194] "AAACCCACATAACTCG-1" "AAACCCACATGTAACC-1" "AAACCCAGTGAGTCAG-1" "AAACCCAGTGCTTATG-1" ...
.. ..@ key : chr "sct_"
.. ..@ assay.orig : NULL
.. ..@ var.features : chr [1:3000] "GNLY" "IGKC" "S100A9" "S100A8" ...
.. ..@ meta.features:'data.frame': 20666 obs. of 6 variables:
.. .. ..$ sct.detection_rate : num [1:20666] 0.003924 0.051893 0.001177 0.000687 0.067393 ...
.. .. ..$ sct.gmean : num [1:20666] 0.002724 0.038556 0.000816 0.000476 0.050365 ...
.. .. ..$ sct.variance : num [1:20666] 0.003909 0.064675 0.001176 0.000686 0.081901 ...
.. .. ..$ sct.residual_mean : num [1:20666] -0.00392 -0.01045 0.0048 -0.00904 -0.00616 ...
.. .. ..$ sct.residual_variance: num [1:20666] 0.779 0.894 1.275 0.75 0.965 ...
.. .. ..$ sct.variable : logi [1:20666] FALSE FALSE FALSE FALSE FALSE FALSE ...
.. ..@ misc :List of 2
.. .. ..$ vst.out :List of 12
.. .. .. ..$ model_str : chr "y ~ log_umi"
.. .. .. ..$ model_pars : num [1:2000, 1:3] 0.137 14.691 2.243 2.874 0.746 ...
.. .. .. .. ..- attr(*, "dimnames")=List of 2
.. .. .. .. .. ..$ : chr [1:2000] "B9D1" "XRCC5" "RPS12" "RPS3A" ...
.. .. .. .. .. ..$ : chr [1:3] "theta" "(Intercept)" "log_umi"
.. .. .. ..$ model_pars_outliers : logi [1:2000] FALSE FALSE FALSE FALSE FALSE FALSE ...
.. .. .. ..$ model_pars_fit : num [1:20666, 1:3] 0.0475 0.4904 0.0527 0.0326 0.6443 ...
.. .. .. .. ..- attr(*, "dimnames")=List of 2
.. .. .. .. .. ..$ : chr [1:20666] "AL627309.1" "AL627309.5" "AL627309.4" "AL669831.2" ...
.. .. .. .. .. ..$ : chr [1:3] "theta" "(Intercept)" "log_umi"
.. .. .. .. ..- attr(*, "outliers")= logi [1:2000] FALSE FALSE FALSE FALSE FALSE FALSE ...
.. .. .. ..$ model_str_nonreg : chr ""
.. .. .. ..$ model_pars_nonreg : NULL
.. .. .. ..$ arguments :List of 24
.. .. .. .. ..$ latent_var : chr "log_umi"
.. .. .. .. ..$ batch_var : NULL
.. .. .. .. ..$ latent_var_nonreg : NULL
.. .. .. .. ..$ n_genes : num 2000
.. .. .. .. ..$ n_cells : num 5000
.. .. .. .. ..$ method : chr "poisson"
.. .. .. .. ..$ do_regularize : logi TRUE
.. .. .. .. ..$ theta_regularization: chr "od_factor"
.. .. .. .. ..$ res_clip_range : num [1:2] -101 101
.. .. .. .. ..$ 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"
.. .. .. .. ..$ theta_given : NULL
.. .. .. .. ..$ verbosity : num 2
.. .. .. .. ..$ verbose : NULL
.. .. .. .. ..$ show_progress : NULL
.. .. .. .. ..$ sct.clip.range : num [1:2] -18.4 18.4
.. .. .. ..$ genes_log_gmean_step1: Named num [1:2000] -2.4848 0.0795 1.6421 1.4171 -0.0858 ...
.. .. .. .. ..- attr(*, "names")= chr [1:2000] "B9D1" "XRCC5" "RPS12" "RPS3A" ...
.. .. .. ..$ cells_step1 : chr [1:5000] "CATGAGTTCGCGTCGA-1" "TCGCAGGCAGTCGTTA-1" "TCGTGCTAGGTTAAAC-1" "TTTGATCTCTCGCTTG-1" ...
.. .. .. ..$ cell_attr :'data.frame': 10194 obs. of 10 variables:
.. .. .. .. ..$ orig.ident : Factor w/ 1 level "10x10kPBMCdualIndex": 1 1 1 1 1 1 1 1 1 1 ...
.. .. .. .. ..$ nCount_RNA : num [1:10194] 22575 7758 21733 860 15311 ...
.. .. .. .. ..$ nFeature_RNA : int [1:10194] 4803 2233 4324 343 4143 2332 2235 2171 5218 3199 ...
.. .. .. .. ..$ nCount_spliced : num [1:10194] 15555 4838 14972 225 9914 ...
.. .. .. .. ..$ nFeature_spliced : int [1:10194] 3840 1625 3503 182 3248 1747 1709 1650 4242 2502 ...
.. .. .. .. ..$ nCount_unspliced : num [1:10194] 12648 7323 10260 1509 12001 ...
.. .. .. .. ..$ nFeature_unspliced: int [1:10194] 3837 2561 3091 918 3813 2375 2261 1975 3778 2856 ...
.. .. .. .. ..$ percent.mt : num [1:10194] 5.33 8.84 6.32 31.51 7.91 ...
.. .. .. .. ..$ umi : num [1:10194] 22575 7758 21733 860 15311 ...
.. .. .. .. ..$ log_umi : num [1:10194] 4.35 3.89 4.34 2.93 4.19 ...
.. .. .. ..$ gene_attr :'data.frame': 20666 obs. of 5 variables:
.. .. .. .. ..$ detection_rate : num [1:20666] 0.003924 0.051893 0.001177 0.000687 0.067393 ...
.. .. .. .. ..$ gmean : num [1:20666] 0.002724 0.038556 0.000816 0.000476 0.050365 ...
.. .. .. .. ..$ variance : num [1:20666] 0.003909 0.064675 0.001176 0.000686 0.081901 ...
.. .. .. .. ..$ residual_mean : num [1:20666] -0.00392 -0.01045 0.0048 -0.00904 -0.00616 ...
.. .. .. .. ..$ residual_variance: num [1:20666] 0.779 0.894 1.275 0.75 0.965 ...
.. .. .. ..$ times :List of 7
.. .. .. .. ..$ start_time : POSIXct[1:1], format: "2020-12-12 19:54:11"
.. .. .. .. ..$ get_model_pars: POSIXct[1:1], format: "2020-12-12 19:54:15"
.. .. .. .. ..$ reg_model_pars: POSIXct[1:1], format: "2020-12-12 19:54:47"
.. .. .. .. ..$ get_residuals : POSIXct[1:1], format: "2020-12-12 19:54:47"
.. .. .. .. ..$ correct_umi : POSIXct[1:1], format: "2020-12-12 19:54:58"
.. .. .. .. ..$ get_gene_attr : POSIXct[1:1], format: "2020-12-12 19:55:11"
.. .. .. .. ..$ done : POSIXct[1:1], format: "2020-12-12 19:55:15"
.. .. ..$ umi.assay: chr "RNA"
I converted this Seurat obj to Anndata by sceasy as follows;
> convertFormat(pbmc10k, from = "seurat", to="anndata", outFile = "pbmc10k.h5ad")
... storing 'Phase' as categorical
... storing 'hpca.fine' as categorical
... storing 'hpca.main' as categorical
... storing 'monaco.main' as categorical
... storing 'monaco.fine' as categorical
AnnData object with n_obs × n_vars = 10194 × 36601
obs: 'nCount_RNA', 'nFeature_RNA', 'nCount_spliced', 'nFeature_spliced', 'nCount_unspliced', 'nFeature_unspliced', 'percent.mt', 'nCount_SCT', 'nFeature_SCT', 'SCT_snn_res.0.8', 'seurat_clusters', 'S.Score', 'G2M.Score', 'Phase', 'old.ident', 'hpca.fine', 'hpca.main', 'monaco.main', 'monaco.fine'
var: 'vst.mean', 'vst.variance', 'vst.variance.expected', 'vst.variance.standardized', 'vst.variable'
obsm: 'X_pca', 'X_umap'
Warning message:
In .regularise_df(obj@meta.data, drop_single_values = drop_single_values) :
Dropping single category variables:orig.ident
As you can see, for some reasons, the conversion did not pick up $spliced and $unspliced as vars but instead, it picked $RNA@meta.features as vars. I would appreciate any explanation for this and any pointers to fix this.
Thanks.
