In C3BI-pasteur-fr/UTechSCB-SCHNAPPs: Single Cell Shiny Application for Analysing Single Cell Transcriptomics Data

knitr::opts_chunk$set(echo = TRUE)

library(SeuratDisk)
library(anndata)
library(zellkonverter)
library(reticulate)
conda_list()
use_condaenv("r-reticulate")
# conda_install("base", "numpy")
# conda_install("r-reticulate", "numpy")

# Convert("~/Downloads/bb7e90e4-496c-4708-bcc0-e88f5ffd29e0.Output.h5ad", "h5seurat")
# This creates a copy of this .h5ad object reformatted into .h5seurat inside the example_dir directory

adata <- read_h5ad("~/Downloads/bb7e90e4-496c-4708-bcc0-e88f5ffd29e0.Output.h5ad")
# ad$write_h5ad("foo.h5ad") 
 # remotes::install_github("dynverse/anndata")
 # anndata::install_anndata()
 reticulate::py_config()
colnames(adata$obs)
table(adata$obs$"cell_type")
a1 = grep(pattern = "Outlier",x = adata$obs$"cluster_label",invert = T)
a2 = adata[a1][adata[a1]$obs$"cell_type" %in% c("Progenitor cell","Native cell", "Oligodendrocyte precursor cell")]
table(a2$obs$"cell_type",a2$obs$"cluster_label" )
a2
#  [1] "development_stage_ontology_term_id" "indiv_id"                           "brain_region"                      
#  [4] "cortical_area"                      "lamina"                             "cluster_label"                     
#  [7] "ngene"                              "numi"                               "percent_mito"                      
# [10] "percent_ribo"                       "ncount_rna"                         "nfeature_rna"                      
# [13] "tissue_ontology_term_id"            "assay_ontology_term_id"             "disease_ontology_term_id"          
# [16] "cell_type_ontology_term_id"         "ethnicity_ontology_term_id"         "is_primary_data"                   
# [19] "organism_ontology_term_id"          "sex_ontology_term_id"               "cell_type"                         
# [22] "assay"                              "disease"                            "organism"                          
# [25] "sex"                                "tissue"                             "ethnicity"                         
# [28] "development_stage"                  "organ"                              "organ_ontology_term_id"      

 adata$obs_names = paste0("cell",adata$obs_names)

sce  = basiliskRun(fun = function(adata) {
        # Convert back to an SCE:
        zellkonverter::AnnData2SCE(adata, hdf5_backed =F, verbose = T, uns=F)
    }, env = zellkonverterAnnDataEnv(), adata = adata)



 sce = zellkonverter::AnnData2SCE(adata = a2, hdf5_backed =F, verbose = T, uns=F,obs = F)

# This .d5seurat object can then be read in manually
seuratObject <- LoadH5Seurat("~/Downloads/bb7e90e4-496c-4708-bcc0-e88f5ffd29e0.Output.h5seurat")

C3BI-pasteur-fr/UTechSCB-SCHNAPPs documentation built on April 23, 2024, 11:54 a.m.