https://github.com/cellgeni/sceasy

A package to help convert different single-cell data formats to each other
https://github.com/cellgeni/sceasy

Last synced: 3 months ago
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A package to help convert different single-cell data formats to each other

• Host: GitHub
• URL: https://github.com/cellgeni/sceasy
• Owner: cellgeni
• License: gpl-3.0
• Created: 2019-07-17T14:46:01.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2024-02-28T10:07:24.000Z (8 months ago)
• Last Synced: 2024-04-18T05:37:17.310Z (7 months ago)
• Language: R
• Size: 74.2 KB
• Stars: 328
• Watchers: 8
• Forks: 51
• Open Issues: 45
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# sceasy

`sceasy` is a package that helps easy conversion of different single-cell data formats to each other. Converting to AnnData creates a file that can be directly used in [cellxgene](https://github.com/chanzuckerberg/cellxgene) which is an interactive explorer for single-cell transcriptomics datasets.

| 💡 for h5da to rds conversion also see [https://github.com/cellgeni/schard](https://github.com/cellgeni/schard) |

| ----------------------------------------------------------------------------------------------- |

> ### Warning

> Before installing the conda packages below please first create a new conda environment EnvironmentName and activate it. Everything else can be installed in R.

## 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')

```