Utility functions • STID

Overview

This vignette introduces four utility functions used for environment configuration, cross-format data conversion, and annotation parsing in STID workflows. configure_conda() prepares the Python environment required by Python-backed conversion steps. h5ad2rds() and rds2h5ad() convert data between AnnData h5ad files and Seurat-compatible R objects. parse_gtf() extracts structured gene annotation information from GTF files.

Function summary

Function	Purpose	Typical input	Typical output	Notes
`configure_conda()`	Configure the Python environment through `reticulate`	Conda environment name, or default Miniconda setup	Activated Python/Conda environment	Run before Python-backed conversion workflows
`h5ad2rds()`	Convert AnnData `h5ad` files to Seurat objects	`.h5ad` file path	Seurat object and/or `.rds` file	Supports spatial and single-cell modes, reductions, coordinates, and optional SCT conversion
`rds2h5ad()`	Convert Seurat objects to AnnData-compatible `h5ad` files	Seurat object	`.h5ad` file	Current helper supports the SeuratDisk conversion path
`parse_gtf()`	Parse GTF annotation files into tidy tables	`.gtf` file path	Data frame containing genomic features and attributes	Use `fil_label` to filter feature types such as `gene`

Prerequisites

library(tidyverse)
library(Seurat)
library(STID)

`configure_conda()`

configure_conda() configures Python through reticulate. If no Conda environment name is supplied, it attempts to use or install the default Miniconda environment. If a Conda environment name is supplied, it checks whether that environment exists before activating it.

# Use default Miniconda
configure_conda()

# Use an existing Conda environment
configure_conda(conda_nm = "scanpy_env")

Run this configuration before using Python-backed conversion workflows such as h5ad2rds() and rds2h5ad().

`h5ad2rds()`

h5ad2rds() converts an AnnData h5ad file into a Seurat object. It supports spatial and single-cell modes, optional reductions, optional spatial coordinates, and optional SCT conversion.

stRNA <- h5ad2rds(
  file_path = "data/sample_spatial.h5ad",
  data_type = "stRNA",
  convert_mode = "scanpy",
  assay_id = "Spatial",
  X_index = "rawX",
  binsize = 100,
  SCT_index = FALSE,
  reduction_index = TRUE,
  image_index = TRUE,
  return_object = TRUE,
  grp_nm = "sample_spatial",
  dir_nm = "M0_h5ad2rds"
)

`rds2h5ad()`

rds2h5ad() converts a Seurat object into an AnnData-compatible h5ad file using the SeuratDisk path.

rds2h5ad(
  seurat_obj = stRNA,
  data_type = "stRNA",
  convert_mode = "seurat",
  assay_id = "Spatial",
  grp_nm = "sample_spatial",
  dir_nm = "M0_rds2h5ad"
)

Note: The Scanpy mode of rds2h5ad() is not implemented in the current helper. Use convert_mode = "seurat" for this direction.

`parse_gtf()`

parse_gtf() reads a GTF file and returns a tidy data frame. The fil_label argument filters the feature column, for example to keep only genes.

gtf_gene <- parse_gtf(
  gtf_file = "reference/annotation.gtf",
  fil_label = "gene"
)

head(gtf_gene)

gene_table <- parse_gtf("reference/annotation.gtf", fil_label = "gene") %>%
  dplyr::select(seqname, start, end, strand, gene_id, gene_name, gene_biotype)

Session information

sessionInfo()
#> R version 4.2.0 (2022-04-22 ucrt)
#> Platform: x86_64-w64-mingw32/x64 (64-bit)
#> Running under: Windows 10 x64 (build 22000)
#> 
#> Matrix products: default
#> 
#> locale:
#> [1] LC_COLLATE=Chinese (Simplified)_China.utf8 
#> [2] LC_CTYPE=Chinese (Simplified)_China.utf8   
#> [3] LC_MONETARY=Chinese (Simplified)_China.utf8
#> [4] LC_NUMERIC=C                               
#> [5] LC_TIME=Chinese (Simplified)_China.utf8    
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> loaded via a namespace (and not attached):
#>  [1] digest_0.6.35     R6_2.6.1          jsonlite_1.8.8    lifecycle_1.0.5  
#>  [5] evaluate_1.0.1    cachem_1.1.0      rlang_1.1.7       cli_3.6.5        
#>  [9] rstudioapi_0.15.0 fs_1.6.3          jquerylib_0.1.4   bslib_0.8.0      
#> [13] ragg_1.3.0        rmarkdown_2.29    pkgdown_2.2.0     textshaping_0.3.6
#> [17] desc_1.4.3        tools_4.2.0       htmlwidgets_1.6.4 yaml_2.3.10      
#> [21] xfun_0.49         fastmap_1.2.0     compiler_4.2.0    systemfonts_1.0.4
#> [25] htmltools_0.5.8.1 knitr_1.49        sass_0.4.9