单细胞之rds，loom和h5ad数据格式转换
Seurat依旧是单细胞分析的利器，也有越来越的的单细胞分析工具基于python开发。在数据分析时，有时需要将seurat的结果迁移到python下游分析，手动迁移seurat的cluster，umap，pca等结果很麻烦，现在和大家分享一款数据格式转换工具，帮助大家完成R与python多平台的多工具的数据分析。
工具来自这篇文章——Comparison of visualization tools for single-cell RNAseq data
这里是github上 README.md
Installation
sceasy is installable either as a bioconda package:
conda install -c bioconda r-sceasy
or as an R package:
devtools::install_github("cellgeni/sceasy")
which will require the biconductor packages BiocManager and LoomExperiment:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install(c("LoomExperiment", "SingleCellExperiment"))
To use sceasy ensure the anndata package is installed:
conda install anndata -c bioconda
Optionally, if you plan to convert between loom and anndata, please also ensure that the loompy package is installed:
conda install loompy -c bioconda
You will also need to install reticulate package:
install.packages('reticulate')
Usage
Before converting your data please load the following libraries in your R session:
library(sceasy)
library(reticulate)
use_condaenv('EnvironmentName')
loompy <- reticulate::import('loompy')
Seurat to AnnData
sceasy::convertFormat(seurat_object, from="seurat", to="anndata",
outFile='filename.h5ad')
AnnData to Seurat
sceasy::convertFormat(h5ad_file, from="anndata", to="seurat",
outFile='filename.rds')
Seurat to SingleCellExperiment
sceasy::convertFormat(seurat_object, from="seurat", to="sce",
outFile='filename.rds')
SingleCellExperiment to AnnData
sceasy::convertFormat(sce_object, from="sce", to="anndata",
outFile='filename.h5ad')
SingleCellExperiment to Loom
sceasy::convertFormat(sce_object, from="sce", to="loom",
outFile='filename.loom')
Loom to AnnData
sceasy::convertFormat('filename.loom', from="loom", to="anndata",
outFile='filename.h5ad')
Loom to SingleCellExperiment
sceasy::convertFormat('filename.loom', from="loom", to="sce",
outFile='filename.rds')
